{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "58ce2dae-3c85-fd72-b53e-8978b11fbf05"
   },
   "source": [
    "An attempt to predict the win probability of the teams in a given match at the end of each over and to look at the important factors affecting the match output.\n",
    "\n",
    "**Objective :** \n",
    "To predict the win probability of SRH at the end of each over for the finals of IPL season 2016.\n",
    "\n",
    "**Training data :**\n",
    "All other matches played during 2016 season \n",
    "\n",
    "Let us first import the necessary modules.!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "5c400947-b70d-5b6b-faae-62b476c256e3"
   },
   "outputs": [],
   "source": [
    "import operator\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import xgboost as xgb\n",
    "import seaborn as sns\n",
    "%matplotlib inline\n",
    "\n",
    "pd.set_option('display.max_columns', 50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "52f5a7d5-85bd-1f61-21e0-fce7d029c9b0"
   },
   "source": [
    "Load the dataset and look at the top few rows to get an idea about the data. \n",
    "\n",
    "If you want to know more about the data, please look at the kernel here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_cell_guid": "1bae504f-7cdf-52e6-75ef-3055d008fcba"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>bowling_team</th>\n",
       "      <th>over</th>\n",
       "      <th>ball</th>\n",
       "      <th>batsman</th>\n",
       "      <th>non_striker</th>\n",
       "      <th>bowler</th>\n",
       "      <th>is_super_over</th>\n",
       "      <th>wide_runs</th>\n",
       "      <th>bye_runs</th>\n",
       "      <th>legbye_runs</th>\n",
       "      <th>noball_runs</th>\n",
       "      <th>penalty_runs</th>\n",
       "      <th>batsman_runs</th>\n",
       "      <th>extra_runs</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>dismissal_kind</th>\n",
       "      <th>fielder</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>BB McCullum</td>\n",
       "      <td>SC Ganguly</td>\n",
       "      <td>P Kumar</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning           batting_team                 bowling_team  over  \\\n",
       "0         1       1  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "1         1       1  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "2         1       1  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "3         1       1  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "4         1       1  Kolkata Knight Riders  Royal Challengers Bangalore     1   \n",
       "\n",
       "   ball      batsman  non_striker   bowler  is_super_over  wide_runs  \\\n",
       "0     1   SC Ganguly  BB McCullum  P Kumar              0          0   \n",
       "1     2  BB McCullum   SC Ganguly  P Kumar              0          0   \n",
       "2     3  BB McCullum   SC Ganguly  P Kumar              0          1   \n",
       "3     4  BB McCullum   SC Ganguly  P Kumar              0          0   \n",
       "4     5  BB McCullum   SC Ganguly  P Kumar              0          0   \n",
       "\n",
       "   bye_runs  legbye_runs  noball_runs  penalty_runs  batsman_runs  extra_runs  \\\n",
       "0         0            1            0             0             0           1   \n",
       "1         0            0            0             0             0           0   \n",
       "2         0            0            0             0             0           1   \n",
       "3         0            0            0             0             0           0   \n",
       "4         0            0            0             0             0           0   \n",
       "\n",
       "   total_runs player_dismissed dismissal_kind fielder  \n",
       "0           1              NaN            NaN     NaN  \n",
       "1           0              NaN            NaN     NaN  \n",
       "2           1              NaN            NaN     NaN  \n",
       "3           0              NaN            NaN     NaN  \n",
       "4           0              NaN            NaN     NaN  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_path = \"../input/\"\n",
    "score_df = pd.read_csv(data_path+\"deliveries.csv\")\n",
    "match_df = pd.read_csv(data_path+\"matches.csv\")\n",
    "score_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "7e3c8738-6d2b-3d93-0065-061852b8c26f"
   },
   "source": [
    "In this analysis, we are going to look at the matches played only during the latest season 2016. So let us subset the dataset to get only these rows. \n",
    "\n",
    "Also some matches are affected by rain and hence Duckworth-Lewis method are used for these matches and so using these matches for training our model might cause some error in our training and so let us neglect those matches as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_cell_guid": "ac97ab74-f728-9296-ac8c-c9c3556ca4f7"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>season</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>toss_winner</th>\n",
       "      <th>toss_decision</th>\n",
       "      <th>result</th>\n",
       "      <th>dl_applied</th>\n",
       "      <th>winner</th>\n",
       "      <th>win_by_runs</th>\n",
       "      <th>win_by_wickets</th>\n",
       "      <th>player_of_match</th>\n",
       "      <th>venue</th>\n",
       "      <th>umpire1</th>\n",
       "      <th>umpire2</th>\n",
       "      <th>umpire3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>517</th>\n",
       "      <td>518</td>\n",
       "      <td>2016</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>2016-04-09</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>bat</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>AM Rahane</td>\n",
       "      <td>Wankhede Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>CK Nandan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>518</th>\n",
       "      <td>519</td>\n",
       "      <td>2016</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2016-04-10</td>\n",
       "      <td>Delhi Daredevils</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>AD Russell</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>C Shamshuddin</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>519</th>\n",
       "      <td>520</td>\n",
       "      <td>2016</td>\n",
       "      <td>Chandigarh</td>\n",
       "      <td>2016-04-11</td>\n",
       "      <td>Kings XI Punjab</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Gujarat Lions</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>AJ Finch</td>\n",
       "      <td>Punjab Cricket Association IS Bindra Stadium, ...</td>\n",
       "      <td>AK Chaudhary</td>\n",
       "      <td>VA Kulkarni</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>520</th>\n",
       "      <td>521</td>\n",
       "      <td>2016</td>\n",
       "      <td>Bangalore</td>\n",
       "      <td>2016-04-12</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>Sunrisers Hyderabad</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Royal Challengers Bangalore</td>\n",
       "      <td>45</td>\n",
       "      <td>0</td>\n",
       "      <td>AB de Villiers</td>\n",
       "      <td>M Chinnaswamy Stadium</td>\n",
       "      <td>HDPK Dharmasena</td>\n",
       "      <td>VK Sharma</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>521</th>\n",
       "      <td>522</td>\n",
       "      <td>2016</td>\n",
       "      <td>Kolkata</td>\n",
       "      <td>2016-04-13</td>\n",
       "      <td>Kolkata Knight Riders</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>field</td>\n",
       "      <td>normal</td>\n",
       "      <td>0</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>RG Sharma</td>\n",
       "      <td>Eden Gardens</td>\n",
       "      <td>Nitin Menon</td>\n",
       "      <td>S Ravi</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id  season        city        date                        team1  \\\n",
       "517  518    2016      Mumbai  2016-04-09               Mumbai Indians   \n",
       "518  519    2016     Kolkata  2016-04-10             Delhi Daredevils   \n",
       "519  520    2016  Chandigarh  2016-04-11              Kings XI Punjab   \n",
       "520  521    2016   Bangalore  2016-04-12  Royal Challengers Bangalore   \n",
       "521  522    2016     Kolkata  2016-04-13        Kolkata Knight Riders   \n",
       "\n",
       "                       team2            toss_winner toss_decision  result  \\\n",
       "517  Rising Pune Supergiants         Mumbai Indians           bat  normal   \n",
       "518    Kolkata Knight Riders  Kolkata Knight Riders         field  normal   \n",
       "519            Gujarat Lions          Gujarat Lions         field  normal   \n",
       "520      Sunrisers Hyderabad    Sunrisers Hyderabad         field  normal   \n",
       "521           Mumbai Indians         Mumbai Indians         field  normal   \n",
       "\n",
       "     dl_applied                       winner  win_by_runs  win_by_wickets  \\\n",
       "517           0      Rising Pune Supergiants            0               9   \n",
       "518           0        Kolkata Knight Riders            0               9   \n",
       "519           0                Gujarat Lions            0               5   \n",
       "520           0  Royal Challengers Bangalore           45               0   \n",
       "521           0               Mumbai Indians            0               6   \n",
       "\n",
       "    player_of_match                                              venue  \\\n",
       "517       AM Rahane                                   Wankhede Stadium   \n",
       "518      AD Russell                                       Eden Gardens   \n",
       "519        AJ Finch  Punjab Cricket Association IS Bindra Stadium, ...   \n",
       "520  AB de Villiers                              M Chinnaswamy Stadium   \n",
       "521       RG Sharma                                       Eden Gardens   \n",
       "\n",
       "             umpire1        umpire2  umpire3  \n",
       "517  HDPK Dharmasena      CK Nandan      NaN  \n",
       "518           S Ravi  C Shamshuddin      NaN  \n",
       "519     AK Chaudhary    VA Kulkarni      NaN  \n",
       "520  HDPK Dharmasena      VK Sharma      NaN  \n",
       "521      Nitin Menon         S Ravi      NaN  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let us take only the matches played in 2016 for this analysis #\n",
    "match_df = match_df.ix[match_df.season==2016,:]\n",
    "match_df = match_df.ix[match_df.dl_applied == 0,:]\n",
    "match_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "03300b11-333f-ae10-b40c-86838a5c88a7"
   },
   "source": [
    "Okay. Now that we are done with the pre-processing, let us create the variables that are needed for building our model. \n",
    "\n",
    "Some of the important variables which I could think of are the following:\n",
    "\n",
    "1. Runs scored in the last over\n",
    "2. Wickets taken in the last over\n",
    "3. Total score of the innings\n",
    "4. Total wickets \n",
    "5. Target that the team is chasing down\n",
    "6. Remaining target\n",
    "7. Run rate\n",
    "8. Required run rate\n",
    "9. Difference between run rate and required run rate\n",
    "10. Binary variables on whether the team for which we are predicting is batting team or bowling team\n",
    "\n",
    "There are several other variables which we can create including\n",
    "\n",
    "1. Team name\n",
    "2. Opponent team name\n",
    "3. Score in the last 'n' overs\n",
    "4. Players who are batting\n",
    "5. Player who is bowling and so on.\n",
    "\n",
    "But ours is a good set of variables to start with.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_cell_guid": "7f3ec7e6-ce62-5a88-8b0d-b1875f628143"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/conda/lib/python3.5/site-packages/pandas/core/indexing.py:132: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>match_id</th>\n",
       "      <th>inning</th>\n",
       "      <th>over</th>\n",
       "      <th>team1</th>\n",
       "      <th>team2</th>\n",
       "      <th>batting_team</th>\n",
       "      <th>winner</th>\n",
       "      <th>total_runs</th>\n",
       "      <th>player_dismissed</th>\n",
       "      <th>innings_wickets</th>\n",
       "      <th>innings_score</th>\n",
       "      <th>score_target</th>\n",
       "      <th>remaining_target</th>\n",
       "      <th>run_rate</th>\n",
       "      <th>required_run_rate</th>\n",
       "      <th>runrate_diff</th>\n",
       "      <th>is_batting_team</th>\n",
       "      <th>target</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>518</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>518</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>12</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>518</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>8</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>6.666667</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>518</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>29</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>7.250000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>518</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>Mumbai Indians</td>\n",
       "      <td>Rising Pune Supergiants</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4</td>\n",
       "      <td>30</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>-1.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   match_id  inning  over           team1                    team2  \\\n",
       "0       518       1     1  Mumbai Indians  Rising Pune Supergiants   \n",
       "1       518       1     2  Mumbai Indians  Rising Pune Supergiants   \n",
       "2       518       1     3  Mumbai Indians  Rising Pune Supergiants   \n",
       "3       518       1     4  Mumbai Indians  Rising Pune Supergiants   \n",
       "4       518       1     5  Mumbai Indians  Rising Pune Supergiants   \n",
       "\n",
       "     batting_team                   winner  total_runs  player_dismissed  \\\n",
       "0  Mumbai Indians  Rising Pune Supergiants           8                 0   \n",
       "1  Mumbai Indians  Rising Pune Supergiants           4                 1   \n",
       "2  Mumbai Indians  Rising Pune Supergiants           8                 0   \n",
       "3  Mumbai Indians  Rising Pune Supergiants           9                 1   \n",
       "4  Mumbai Indians  Rising Pune Supergiants           1                 2   \n",
       "\n",
       "   innings_wickets  innings_score  score_target  remaining_target  run_rate  \\\n",
       "0                0              8          -1.0              -1.0  8.000000   \n",
       "1                1             12          -1.0              -1.0  6.000000   \n",
       "2                1             20          -1.0              -1.0  6.666667   \n",
       "3                2             29          -1.0              -1.0  7.250000   \n",
       "4                4             30          -1.0              -1.0  6.000000   \n",
       "\n",
       "   required_run_rate  runrate_diff  is_batting_team  target  \n",
       "0               -1.0          -1.0                1       0  \n",
       "1               -1.0          -1.0                1       0  \n",
       "2               -1.0          -1.0                1       0  \n",
       "3               -1.0          -1.0                1       0  \n",
       "4               -1.0          -1.0                1       0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# runs and wickets per over #\n",
    "score_df = pd.merge(score_df, match_df[['id','season', 'winner', 'result', 'dl_applied', 'team1', 'team2']], left_on='match_id', right_on='id')\n",
    "score_df.player_dismissed.fillna(0, inplace=True)\n",
    "score_df['player_dismissed'].ix[score_df['player_dismissed'] != 0] = 1\n",
    "train_df = score_df.groupby(['match_id', 'inning', 'over', 'team1', 'team2', 'batting_team', 'winner'])[['total_runs', 'player_dismissed']].agg(['sum']).reset_index()\n",
    "train_df.columns = train_df.columns.get_level_values(0)\n",
    "\n",
    "# innings score and wickets #\n",
    "train_df['innings_wickets'] = train_df.groupby(['match_id', 'inning'])['player_dismissed'].cumsum()\n",
    "train_df['innings_score'] = train_df.groupby(['match_id', 'inning'])['total_runs'].cumsum()\n",
    "train_df.head()\n",
    "\n",
    "# Get the target column #\n",
    "temp_df = train_df.groupby(['match_id', 'inning'])['total_runs'].sum().reset_index()\n",
    "temp_df = temp_df.ix[temp_df['inning']==1,:]\n",
    "temp_df['inning'] = 2\n",
    "temp_df.columns = ['match_id', 'inning', 'score_target']\n",
    "train_df = train_df.merge(temp_df, how='left', on = ['match_id', 'inning'])\n",
    "train_df['score_target'].fillna(-1, inplace=True)\n",
    "\n",
    "# get the remaining target #\n",
    "def get_remaining_target(row):\n",
    "    if row['score_target'] == -1.:\n",
    "        return -1\n",
    "    else:\n",
    "        return row['score_target'] - row['innings_score']\n",
    "\n",
    "train_df['remaining_target'] = train_df.apply(lambda row: get_remaining_target(row),axis=1)\n",
    "\n",
    "# get the run rate #\n",
    "train_df['run_rate'] = train_df['innings_score'] / train_df['over']\n",
    "\n",
    "# get the remaining run rate #\n",
    "def get_required_rr(row):\n",
    "    if row['remaining_target'] == -1:\n",
    "        return -1.\n",
    "    elif row['over'] == 20:\n",
    "        return 99\n",
    "    else:\n",
    "        return row['remaining_target'] / (20-row['over'])\n",
    "    \n",
    "train_df['required_run_rate'] = train_df.apply(lambda row: get_required_rr(row), axis=1)\n",
    "\n",
    "def get_rr_diff(row):\n",
    "    if row['inning'] == 1:\n",
    "        return -1\n",
    "    else:\n",
    "        return row['run_rate'] - row['required_run_rate']\n",
    "    \n",
    "train_df['runrate_diff'] = train_df.apply(lambda row: get_rr_diff(row), axis=1)\n",
    "train_df['is_batting_team'] = (train_df['team1'] == train_df['batting_team']).astype('int')\n",
    "train_df['target'] = (train_df['team1'] == train_df['winner']).astype('int')\n",
    "\n",
    "train_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "f0f5e550-c332-1207-b4c6-cd5d7495bc11"
   },
   "source": [
    "Now let us split the data and keep the final match as our validation sample."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_cell_guid": "f2aa3ce2-9d82-a78d-a06c-19e042151057"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2135, 12) (2135,)\n",
      "(39, 12) (39,)\n"
     ]
    }
   ],
   "source": [
    "x_cols = ['inning', 'over', 'total_runs', 'player_dismissed', 'innings_wickets', 'innings_score', 'score_target', 'remaining_target', 'run_rate', 'required_run_rate', 'runrate_diff', 'is_batting_team']\n",
    "\n",
    "# let us take all the matches but for the final as development sample and final as val sample #\n",
    "val_df = train_df.ix[train_df.match_id == 577,:]\n",
    "dev_df = train_df.ix[train_df.match_id != 577,:]\n",
    "\n",
    "# create the input and target variables #\n",
    "dev_X = np.array(dev_df[x_cols[:]])\n",
    "dev_y = np.array(dev_df['target'])\n",
    "val_X = np.array(val_df[x_cols[:]])[:-1,:]\n",
    "val_y = np.array(val_df['target'])[:-1]\n",
    "print(dev_X.shape, dev_y.shape)\n",
    "print(val_X.shape, val_y.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "9709633c-2fb0-997e-4784-aba1a934d7b8"
   },
   "source": [
    "We shall use Xgboost for our modeling. Let us create a custom function for the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_cell_guid": "0fce6c9f-a857-c8e0-036b-5d082d4590fa"
   },
   "outputs": [],
   "source": [
    "# define the function to create the model #\n",
    "def runXGB(train_X, train_y, seed_val=0):\n",
    "    param = {}\n",
    "    param['objective'] = 'binary:logistic'\n",
    "    param['eta'] = 0.05\n",
    "    param['max_depth'] = 8\n",
    "    param['silent'] = 1\n",
    "    param['eval_metric'] = \"auc\"\n",
    "    param['min_child_weight'] = 1\n",
    "    param['subsample'] = 0.7\n",
    "    param['colsample_bytree'] = 0.7\n",
    "    param['seed'] = seed_val\n",
    "    num_rounds = 100\n",
    "\n",
    "    plst = list(param.items())\n",
    "    xgtrain = xgb.DMatrix(train_X, label=train_y)\n",
    "    model = xgb.train(plst, xgtrain, num_rounds)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "6a24a8fb-ff95-9f60-3cfd-6b201c3d04b4"
   },
   "source": [
    "Now we are all set to build our model and make predictions. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_cell_guid": "e9befe1c-e42e-3aa9-49d9-1a8bae172d8d"
   },
   "outputs": [],
   "source": [
    "# let us build the model and get predcition for the final match #\n",
    "model = runXGB(dev_X, dev_y)\n",
    "xgtest = xgb.DMatrix(val_X)\n",
    "preds = model.predict(xgtest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "f9d64763-f04b-72f8-2c6c-ab818058439b"
   },
   "source": [
    "**Important variables:**\n",
    "\n",
    "Now that we have built our model, let us look at the important variables that contribute to the win."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_cell_guid": "8c98ff26-b8c7-a9fc-a0f3-4b19a2add5d1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA/QAAAKACAYAAAAy4TMBAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZhX0/wEH8AOO4xjtKwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc707a780f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def create_feature_map(features):\n",
    "    outfile = open('xgb.fmap', 'w')\n",
    "    for i, feat in enumerate(features):\n",
    "        outfile.write('{0}\\t{1}\\tq\\n'.format(i,feat))\n",
    "    outfile.close()\n",
    "\n",
    "create_feature_map(x_cols)\n",
    "importance = model.get_fscore(fmap='xgb.fmap')\n",
    "importance = sorted(importance.items(), key=operator.itemgetter(1), reverse=True)\n",
    "imp_df = pd.DataFrame(importance, columns=['feature','fscore'])\n",
    "imp_df['fscore'] = imp_df['fscore'] / imp_df['fscore'].sum()\n",
    "\n",
    "# create a function for labeling #\n",
    "def autolabel(rects):\n",
    "    for rect in rects:\n",
    "        height = rect.get_height()\n",
    "        ax.text(rect.get_x() + rect.get_width()/2., 1.02*height,\n",
    "                '%f' % float(height),\n",
    "                ha='center', va='bottom')\n",
    "        \n",
    "labels = np.array(imp_df.feature.values)\n",
    "ind = np.arange(len(labels))\n",
    "width = 0.9\n",
    "fig, ax = plt.subplots(figsize=(12,6))\n",
    "rects = ax.bar(ind, np.array(imp_df.fscore.values), width=width, color='y')\n",
    "ax.set_xticks(ind+((width)/2.))\n",
    "ax.set_xticklabels(labels, rotation='vertical')\n",
    "ax.set_ylabel(\"Importance score\")\n",
    "ax.set_title(\"Variable importance\")\n",
    "autolabel(rects)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "77c4ab15-d81a-bdd5-1984-65aac07ee5d2"
   },
   "source": [
    "**Run rate** is the most important predictor of the win. It makes sense since if the run rate is high, the team have higher tendency to win.\n",
    "\n",
    "**Innings score** is the second most important predictor with **target score** being the third.\n",
    "\n",
    "**Win probability at the end of each over for SRH:**\n",
    "\n",
    "Now that we had a look at the important predictor variables, let us check the win probability predictions for the final match."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "_cell_guid": "ff0a58eb-5d5e-47ed-4417-87330df0ccdb"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABCYAAAI7CAYAAAAwM5pAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nJEmtsTEhSZIkSZJa8/8BTo9KNvh5LwoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc706b7aa20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "out_df = pd.DataFrame({'Team1':val_df.team1.values})\n",
    "out_df['is_batting_team'] = val_df.is_batting_team.values\n",
    "out_df['innings_over'] = np.array(val_df.apply(lambda row: str(row['inning']) + \"_\" + str(row['over']), axis=1))\n",
    "out_df['innings_score'] = val_df.innings_score.values\n",
    "out_df['innings_wickets'] = val_df.innings_wickets.values\n",
    "out_df['score_target'] = val_df.score_target.values\n",
    "out_df['total_runs'] = val_df.total_runs.values\n",
    "out_df['predictions'] = list(preds)+[1]\n",
    "\n",
    "fig, ax1 = plt.subplots(figsize=(12,6))\n",
    "ax2 = ax1.twinx()\n",
    "labels = np.array(out_df['innings_over'])\n",
    "ind = np.arange(len(labels))\n",
    "width = 0.7\n",
    "rects = ax1.bar(ind, np.array(out_df['innings_score']), width=width, color=['yellow']*20 + ['green']*20)\n",
    "ax1.set_xticks(ind+((width)/2.))\n",
    "ax1.set_xticklabels(labels, rotation='vertical')\n",
    "ax1.set_ylabel(\"Innings score\")\n",
    "ax1.set_xlabel(\"Innings and over\")\n",
    "ax1.set_title(\"Win percentage prediction for Sunrisers Hyderabad - over by over\")\n",
    "\n",
    "ax2.plot(ind+0.35, np.array(out_df['predictions']), color='b', marker='o')\n",
    "ax2.plot(ind+0.35, np.array([0.5]*40), color='red', marker='o')\n",
    "ax2.set_ylabel(\"Win percentage\", color='b')\n",
    "ax2.set_ylim([0,1])\n",
    "ax2.grid(b=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "df8b4b40-904f-0bb3-bc45-2911797e15fe"
   },
   "source": [
    "Yellow bar represents the scores in the corresponding overs played by SRH while green is for RCB. \n",
    "\n",
    "Red line represents the equal win probability and blue line represents the win probability of SRH at the end of each over. \n",
    "\n",
    "As we can see, it was generally below 0.5 for most part of the first innings, but things changed in the last two overs. Then it was continuously above 0.5 for the first 8 overs and was below 0.5 till 15th over. This makes us wonder what has happened in those particular overs which caused the shift in predictions.\n",
    "\n",
    "So let us look at the same graph by using the number of runs scored in that over in place of overall runs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "_cell_guid": "6595d69e-81f4-67bd-316b-3cd7ed1be9c1"
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABB0AAAI7CAYAAACgIOOPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAAPYQAAD2EBqD+naQAAIABJREFUeJzs3XmcHFW5//FP9+xZhoQte8hA8AAxChJICEsAUSATEC8g\n8gNBjVdZvRdRQJGE1QVZVGTVsCqr4kKGTRYhGIPs+z0gJGQPCQnZZp+u3x+nKlPT6Znpmemeru7+\nvl+vvCbTU336dHd1dZ2nnvOcmOd5iIiIiIiIiIhkWjzXHRARERERERGRwqSgg4iIiIiIiIhkhYIO\nIiIiIiIiIpIVCjqIiIiIiIiISFYo6CAiIiIiIiIiWaGgg4iIiIiIiIhkhYIOIiIiIiIiIpIVCjqI\niIiIiIiISFYo6CAiIiIiIiIiWaGgg4ikzRizyBhza677IYUteT8zxkwzxiSMMQdl8DESxphZmWqv\nh499hDHmFWNMgzGmzRhTnYt+5Fou34N8kI39voePf7H/+Nv2w2MV7XeLMeZ2Y8zGXPdDRCSbSnPd\nARHJPmPM8cB9wJettX9N+ttrwETgEGvtM0l/WwwsttYe4N+UALx+6HLBMMZUAecBT1trn811f/JE\nqn2sx/udMeZIYF9r7SWdtNfv+7I/gLsPeBM4A2gCNmf5MScCs4FJwDDgY+Bt4G/W2t9k87G7kZP3\noLeMMRcDs4DtrbVrU/x9EfC6tfboDD5sLl+f/nx/8mY/yIK8+hyIiPSGgg4ixeE5/+cBwJaggzFm\nMDABaAH2B54J/W00MBr4Q6gdgws8SPoG4AZ8HqCgQy9Ya58xxlRZa5t7eNfpuIF9qqBDFdDa5871\n3D7AIODH1tqns/1gxpipwFPAh8AtwEpgDDAF+C6Qy6BDrt6D3upucKiBo4iISAoKOogUAWvtCmPM\nQlzQIWw/IAY8kOJvB+BOov8Zaqclm/3MFmNMpbW2MUcPH8vR4/YrY0wMKLfWNmWj/V4EHKCL176X\n7WXCMP/n+kw1aIwZYK2t7+TPFwKfAJOstR1SuI0x22eqD+kK7yf9/R508zoVvGJ//rnkB00bct2P\nqNDrIVJ8FHQQKR7PAScYYypCA8P9cWnejwDXJW2/VdDBTx9+ylr7Tf/3U4Hb/G2PA07GXdl/HPhv\na+3HXXXIGHM7cCzwGeAmvz/rgZustZclbRsD/gf4FrCLv91fgAustZ8k9fF13BXcK4BPA+cDv/b/\nfjJwtn97E/AGcJm19olQG0cCPwQ+h8vseBY4z1r7doq+G+AG4PNAA3CHv61njNkJWOi/jhf76dkA\nF1trL/XT3r8HHASMxA0OHwZ+kJy+bYw5GLgKl5myFPiFf59Z1tp40rYnA/8L7OH36XG/zaV0IZQ+\nvjtwGXA4Lgvm98D54YCCMSbhv8YLgB8BuwLHA39L973y2/kx8B1gW7+ts1P0axrwNHBweIqKMWYy\nLotkClAOvA/8zlp7nTHmNuBUwPP7CuBZa0tC/b/YWntpqL29gJ8AU3E1j54HLrTWPh/aptf7vDHm\naWAabn940RgDcHvo83Q8bl/dAzfl4lH/dV8eauN23H73WdzrfwDwBPBfnTzszsBbyQEHAGvtmlC7\nwb76dWvtnUn97vBahfaTXYGLgC/hAjwPAmeEA3zd7CfJ7Q4CLvfbG4Hbb17DfZ5eDbU5GZe9MgUo\nA14AfmStnR/aJujjBL+PR/jPb29jzDDgZ8BhwA7AWuDfwHettYs7eR17zA/0vmqt/XLS7RXAR8Dd\n1trT/dtGAdf7fdqMyzB7lBSBsww8/7SPO74djDE30fXx4Bu4z8KngW1wn8XrrLU3peh/t5/5TDDG\nlOD2uVNxWXsrgLuBS4KAlzHmIWAPa+0uKe7/L6DEWrtv6LZuj63GmH/4z+3rwC+BvYGbca95V/2t\noYvvwZ7sT4XweohIYVEhSZHi8RzuBHVy6Lb9gfnAv4AhxphPh/42Ffg/a+260G2dpQ9fh6sLcTFu\nAH4U6aVte7jj0KO4E6AfAC8Cl4QG6IFbgJ8D83Bp4bcCJwGP+idT4TZ3w51MPe5v+yqAMWY2cCfQ\njDsRnwUsBg4N7myM+RowF9iIq8VwKW4QPs8YMzZF3x8DVgPnAv/AnUh9299mNXAa7QOyk/1/D/p/\n/wJQ4z+Xs4B7gK8CdeEn7g+GHwGG+v2eQ/tgz0va9kJc4MMC5wDX4gIiz6RRsDBo637cIP4Cvy/f\nxZ0kJvs8cA1wLy7IsMi/Pa33yhhzGe71fQX4PvAB7j0b0EXfgvt+ATcdaDfciez3cNMIZvib3Az8\n3f//SbjX/WudPXFjzB644NJE3ID0UmAc8A9jzD4p7tKbff5y3GsD8GO/Tzf7j/91XK2HFtzrfgsu\nkDAv6X3zcBcMHsNNlTgX+FMXj/khbqA5oZu+9UR4Pxno9/c+3GBmdortO9tPkt2MG4w+AJyOC6zV\n4z5/ABhjDsW974Nwr/0PcYPcp4wxk1L08QGg0t/ut/5tD+I+O3P8x/mV3174892V7Ywxyf+2Z+tz\nqt8DRxpjhiTdfrT/eHf5z6kSt+9+ARccvRwXTLqSrff7TDz/tI47vhjpHQ9Ow72vV+A+i4uBG4wx\nHQbBPfzM99UcXHDmRdzA+B+41+Ge0Db3AeOMMXsn9XMs7rvyntBt6R5bPWB7XCDnZdw+391UqlK6\n/x5Ma3/qQj69HiJSYJTpIFI8nsOdQB4APOsP/iYDt1lrPzDGrPL/9qZ/xXEi7iQlHauttUcEv/ht\nn22MGZzqCmuSSuBha+05/u83+ldbzjfG/Npau9YYcwAwEzjRWntf6HGexg2+jscNaAK7AIcnZS/s\nghuo/8lae3xo29+EthmIG4DcEr5iZIy5A3gXd5XotKS+32Ot/Yn/+y3GmJf8vt5sra03xvwJd/Xq\ndWvt3UnP/Xpr7TXhG4wxzwN3G2P2t9YGWSaX4Oa+T7XWrvK3ux/4v6T7jsUNRH5krf156PYHcYGX\nM3AD6u68b60NrpzfaFxl9dONMVdZa98Mbfcp4NPWWht6rLTeK3+Q9gPgIWvtl0LbXY57nTtljInj\nBj3LgD07uYq/wBjzLnCYtfae5L+ncAXuO3F/a+2H/uPchTuhvhI4JGn7Hu/z1tonjauV8t/Ao9ba\nl/37luLel9eBaaGrjv/EBcDOoWNdinLgPmvtj9N4XlfhTvZfNcb8GxcIehJX2LSv9RRestYGAbZg\nusZM3EAmbKv9pBPTgd9aa89L6n/YjcCT1tra0OPejCuMeTnuin7YK9bar4W23QY3rez7SZ+9n5Oe\nGG6fSMXDZWYE7sRNb/kK7cEmcMGmRaHMhO8A44HjrbUP+v38LW5/SNan5+9L97gTSOd4cFDS1Kob\njDGP4AIQN/qP0evPfE8ZYz4DnII7lgfH7JuMMauBc40x0/zCyX/FBaFPAF4KNXECLsvtAb+9nh5b\nhwHfsdb+Ls0uV9DN9yDp70+F8HqISIFRpoNIkbDWvoOrWh/UbtgTd3UpOFGZj8t8AJflUEJ7Acqu\neHQ8AQI3sCkBdkqze9cn/f4b3EnYYf7vx+NSgJ8MX13EXS3bxNYDwoXhgIPvy7gBw6V07gu4q4b3\nJj2Oh0u1T34c2PqK3zxcSnu3ktKTK/zHet7v5+f82+O4q0d/CQIO/n0/wGU/hB3r3/eBpP5/BLzX\nSf+TeWz9flzntzs96fZ/pBhIHkd679UXcJk3ydN6fplGH/fCZSH8Mo2gVrf81/gLwJ+DgAOAtXYl\nLmPmAD8QF8jEPh82CdgRuCFc58Ba+zAusFSb4j5bpa2n4n8O9sMNJj6DG/Q9BiwzxhzVi74GPFLv\n+9slvVaQej9J5RNgsjFmRKo/GmP2xE3PuCdp3xqMC6QkLy2Zqo8NuEHVwSmuGKfDwx1LDkvx76Pw\nhtba93Cf55NCz2EoLjDw+9CmRwIrgoCDf99GkvaxDD3/tI47SW10ezxIarPab/NZYGfjChaDe416\n+5nvqem4vl+bdPvVuL7X+v3eiDuOfiVpu68AC0LTBHp6bG0Cbu9hn1N9D5bjfw/2YH9KJR9fDxEp\nIMp0ECku84ED/f/vD3xkrV0Y+tuZob95pBd0AFiS9HswJWNoGvdN4FJsw971f47zf44HhpB0Uu/z\ncAO2sIUpttvZf6x3uujLrrgTqVSpnx6wIem2xhRz+NeR3vMOThgvxl1FCj8HDxf8wL+9CvhPiiaS\nbxuPCyan2tbDDbbSkXz/93Gv3bik2xeluO+upPdeBansHR7LWrvGGLOOru3it/VWN9ulawdcAO7d\nFH97B/eajqHjvtOXfT7ZTrjnk+rx/4/2YGCg1XZTnyPMWvsScJyfUfFZ3KD5HNyAYU9r7f912UDn\nkusfhF+DTaHbF6XZ3nm4gckSP2PoYeDO0DFqV//nnSnuC5AwxmxjrQ0X6exwLLDWNhtjzsdlUKwy\nxizAZZPcGQ7qdWNeqtoHxphUxWrvBK4zxoyx1i7BDd5K6ThI3InUn9nkQE2fn7/fz3SOO2HdHg+M\nMfvTXmciPFUiaHMj7QG53nzmg0yJ8FS6Tdbazpab3cnvY/JjrTLGfELH4OB9wJeMMVP8DKmdcXUH\nvhvapqfH1mU9zCTq7HswRsfjbjr7Uyr59nqISIFR0EGkuDwHzDCukNhU2rMc8P9/pX+VcX9gubV2\nUZrttnVye6ZWbogDq4D/10mbq5N+721V7DjuhOlk//GSJZ80dfa80/UA7iT9Slxa9iba60T0JhMt\njjuxPILUS5tuSnFbOjqr5ZHqde7pe5Wvsr3Pd6VXK4T4J/0vAS8ZY97DFcQ8Hlc0NOV77GeBdCbd\n1yCtz6O19gFjzLO4oMgXcXP+zzfGfNlaG/5MnEvHaQxhyfv4Vo9trf2VMeZvwDG44oiXAj80xhxi\nre2s3d66F3d1+SRcuvlJwIv+Veueysjzp+/HneQ6Ezvjipm+gwtmLcENOmtxtQMylVX7Au2DYw8X\n5Ogqc22rvnbiIdzr9BVcYcsTcPv2H0Pb9PTYmq2VGfq6PxXa6yEieUJBB5HiEmQuHIgLLIRTLV/C\nDWYOwdV6SFVULBviuCyE8BUT4/8MrtK9j5tiMN/2fknG9/3H2oPUc6WDbWK4+fpP9fJxknU2mBuC\nK2B5kbX2itDt45M2/QhoxF1ZSrZr0u9B/xdZa1NdgUrXrrgChIHgqtaiNO6b7nsVtL9ruF3/amZ3\n2QLB8/w0rgBfZ9I5wQYXCKmnfb8L2x13Up2c2ZBJH+Kej8EVdwszdHwvMuVF/2cwlSG40pw85aA3\n00V6zc82uAk333x73LScC3ED4vf9zTb29fPpZ09cC1xrXL2X13CD+VP60m6Kx1lnjKkDTjLG3I07\n7n43abMPcatMJNst6fc+P/8eHHfCOjseBMfno3HTAI6y1i4Ltfn5pHb68pkHF8isCv2enBmQ/Fhx\n/7HCNWd2xO3j4WlU9caYucDxxphzcYPtef70qkCmjq2d6ep7cFGor+nsT6nk2+shIgVGNR1EisuL\nuMDCSbil0rZkOvhzyV/BTbEYQPpTKzLhrBS/N9M+oLwfFySdlXxHY0yJXxyuO3/BDUJnGbekYyqP\n4aZQ/MhPRU9+rO3TeJxk9f7P5MFccJU4+Th8DqHBsrU2gbuKeIwxZnioL+PZumjcg7gBcqoVBDDG\nbJtGf2O0T7MJfNfvU3INiVTSfa+ewGWOJC+Xdw7dexk34Pnfbt77zf7jdrlqh/8aP45LKd6ygoFx\nSyueiDvh7m2WSDpexAWXTjPGlIUe/0hc0GNubxs2bqnVVII6ERa2zOVew9Z1Ac4k/eBNrxlj4snv\nk3VLei7H1XcBFxh9H/i+cUVfk9vo9vNpjKkybonBsIW49P/k2zPlLlxQ4Re4ff6+pL8/DIw0xhwb\n6ucAXMHRsD4/f9I87oR0dTx41P89yADb0qb/ufx60v368pnHWvsva+1ToX+Lutj8Yb/v/5t0+7l+\n35OD6vfhvhO/hZuCdG/S3zNxbO1OZ9+DTybd3t3+lEo+vh4iUkCU6SBSRKy1LcaYF3CZDo10rE4N\nLggRnISkG3TobACfbpp5E3CEMeZ2XJGs6bjCalcE9RKstc8aV6H9Ar+Y2uO4pQU/hStc+F3al6FM\nyVr7vjHmCtxShfOMq7LdBOyDm296obV2o3FLvN0JvGyMuRd3FXwsbpD2HOldVQo/bqMx5m3gBD+l\nfS3wprX2LT+V/DxjTDluJYYv4ubvJr92F/t/m2+MuRF37D4TeBN3Qhg81gfGmB8DPzFuzfe/4AZT\nO+NSyW/GLV3YnRpjzF9xg4qpuCDV7621b6TxfNN6r/x53Ff5283FnRTvhQukpJqCseU1sdZ6/vv0\nN9yqDLfhlprbDbfG/JH+pi/597vOGPMY0GZDK2ok+TGuYNs/jTE34AZn38ZdwT0vadu+7vMdtrPW\ntvp1Bm7FrSxzDzAc91p9QN8K7V3nD2D/jKsPUY67OvoVv+3bQtv+Dvd+/BYXCDmI9jon2TYYWGqM\n+SPtKf9fwBXZ/B5sed+/hdtX3vLf92XAKFyG1nrcUphd+RSuyOn9uBUfWnFLk+5Ix6UDM6kOV8T3\neNwKBWuS/v5b3ADzLuOWvVyBW961Q72CTDx//xiX7nEn0N3xIPiMz/U/+4Nxg9VVuP04eOyefuZ7\nzVr7unGrDn3br2HxDC6D7xTc8eeZpLs8jNvnrsLtEw8mtZepY2tnuv0eDOluf9pKHr4eIlJglOkg\nUnyewwUVXrTWtiT97Z+0F0xMNWfYY+urYZ1dBU336mgr7qRzOG6O8d7AxdbaDlfKrVvC8tu4on9X\nAD8BDsYFCMJLvKXqY9DGbOCbuKUuL8fNCR5L6EqSdcsrfh5YiptT/kvcnNZX6DhA6+o5Jt8+E3dy\nfw1uNYTgiub/w2VXnOE/nybciWaH52Dd0opH4AIWl/rP4WK/3x2K1/nLlx2LGzTPwl0Nm4EbMPyt\nk/4m9/0Evy8/9fvza9wgInm7zl7ntN4ra+2FuCtle+Le+xrcAGhzirY7/G6tfRw30LK4QenVuLTx\n8HN80O/74f5jh5csTX6N38YF494ALsAtr7oQONha+yId9XWf32o7a+0duNe9DDdX+7+BPwEHWmuT\nC5j2JPPgXFzG0JG41+hq3ED+N8CUpLYvxQUejsUtIRkjxf7YQ13dN/y3elz1/s/i9u1rcAGP0621\nvwru4A+O9sPN7z8T9/6eihuoJ1fmT2UJbj+YhtsvfwIMwi1X+ZcePK/uns8W/nH2Pv9vWxWBtNY2\n4Pbdx3DBhwtxKz8kB7sy8fzBZe90e9zxJejmeGCtfRe3zyRwx5tv46bI/DpF/3vyme+rmf5jTcK9\nNgfjjkcnpuhXE+7YMQh4KtVAvofH1p4+lxbS+B70+9Hl/tSFfHo9RKTAxDxPxwERyQ3/St2x1tou\n098lNWPMn3FX9lPVIuhNe7NxJ487pKrOLyK9Y4y5BhcsHG7dcpgivab9SUTyTSSmVxhjfoirVr0b\nrsLtfOB8P3oebHMbLpof9qi1NnndeBGRgmOMqQyfXBpjdsWl4CZnX4hIhPg1JE4G/qgBovSV9ieR\n4mCMORD4AS7zaQRwjLW2y4xVv47T1bi6L4txU7TuyHJX0xKJoAMupfU63BzSUlwK3+PGmN39tMPA\nI7jCRMG8w95WsRcRyTcf+PN9P8DNvz4NN7XiFznsk4h0whizA64uxXHAtqSYbiCSLu1PIkVnIPAq\nMIdu6pYBGGPG4QpP34CbvnsY8DtjzHJr7d+z2M+0RCLokJytYIz5Oq6S9950LGbXZK0tlDXeRcTR\nHK/0PAJ8FTfntwmXEfYja+37Xd5LRHJlD+D3uIKKZ1trO1uqVyQd2p9Eioi19lH8VYK6WHUt7HTg\nA2ttUA/IGmMOwK0QpKBDJ4bgBiLJc4oPNsaswq0n/hTwY807Fslf1tpvAN/IdT/ygbV2Zj88xiW4\n4poi0kd+0UcV7JaM0P4kIt2YgluaOOwx0i8ynFWRO3j5kZxfAs/51cQDj+CW9jkUV9F5GvBwmpEf\nERERERERkUI0HJcJFbYKqPZrweRUFDMdbsClkO0fvtFae3/o17eMMW8A7+OW/Hm633onIiIiIiIi\nImmJVNDBGPMbXDX2A621K7ra1lq70BizBhhPmkEHz/O8WEyJESIiIiIiItJz994LJ56Y3nYnnLDl\n12wPQlcCw5JuGwZssNbmfPGFyAQd/IDDl4Bp1trFaWw/GtgO6DI4EbZ27Wbi8c7f75KSONXVVWzY\n0EBbWyLdZtOSr21nu331PTft52vb2W5ffc9N+/nadrbbV99z036+tp3t9tX33LSfr21nu331PTft\n52vbmW6/rCwOVHW73eDBDaxb5x5r6NCBfXrMNPwLODLpti/6t+dcJIIOxpgbgBOBo4HNxpggSrPe\nWttojBkIzAb+hIvijAd+DryLK5CRlkTCI5HovlB+W1uC1tbM7+z53Ha221ffc9N+vrad7fbV99y0\nn69tZ7t99T037edr29luX33PTfv52na221ffc9N+vradifY/+ijGFVeUd7tdTU2CSZNaaW3t3eP4\n49/xtGdI7GyM+Syw1lq7xBjzU2CktfZU/+83AWcaY34O3Ap8HrfE7nQiICqFJE8DqoF/AMtD/77i\n/70N+AzwV8ACvwVeAA6y1rb0d2dFRERERESkeLz3Xpzp0wfwyisl/i2pL2bH4x6zZjXRx1n9k4BX\ngJf8B7oaeJn2VcaGA2OCja21i4Ba4DDgVdxSmTOttckrWuREJDIdrLVdBj+stY3AEf3UHRERERER\nEREA5s8v4dRTq1i/3kUSzj67ib32SnDZZRUsXNg+lK2pSTBrVhO1tb1McfB1t0yuv+x88m3PAnv3\n6YGzJBJBBxEREREREZGoeeCBUv73fytpaYlRUuLx8583ccopLtm+traVF14oZdOmKgYPbmDSpNa+\nZjgUJAUdREREREREREI8D66+upwrr6wAYOBAjzlzGjj00LYt28RiMHVqgqFDYd26RK9rOBQ6BR1E\nREREREREfM3NcO65ldx3XxkAI0Yk+MMfGvj0p7NX5LKQKeggIiIiIiIiAqxfD9/8ZhXz5rmh8oQJ\nbfzhDw2MHNn9KoiSWlRWrxARERERERHJmcWLY8yYMWBLwOHQQ1t56KF6BRz6SEEHERERERERKWqv\nvhrnyCMHYK1bEvPUU5v5/e8bGDQoxx0rAJpeISIiIiIiIkXrkUdKOf30Surr3dITs2Y1cuaZLVqJ\nIkMUdBAREREREZGidMstZVx0UQWeF6OiwuP66xs5+mgtQ5FJCjqIiIiIiIhIUWlrg1mzKvjtb8sB\n2G67BHfc0cC++2qFikxT0EFERERERESKxubNcPrplTz6qFsSc5ddEtx9dz01NSoYmQ0KOoiIiIiI\niEhB8jyYPz/Oxo0weHCcsWM9TjmlildfdQUjJ09u5Y47Gth22xx3tIAp6CAiIiIiIiIFp66ulEsu\nqWDRomDRxipKSz1aW12FyP/6rxZ++ctGKitz18dioKCDiIhIAWpubuatt97o9O8lJXGqq6vYsKGB\ntrbU81cnTJhIeXl5trooIiKyVSbCPvskMrJqRF1dKTNnVpJIdGwsCDgcdVQLN9zQSDye6t6SSQo6\niIiIFKC33nqD5csPYcKErrerru7s/gBPs9dee2e6ayIiIkDqTIRx4xLMnt1EbW3vV5DwPLjkkoqt\nAg5hb75ZoiUx+4mCDiIiIgVqwgTYZ5/e33/dusz1RUREJKyzTIRFi+LMnFnJnDmN1Na24nmu8OPa\ntTE++STW4ee6dalvW70aNm7sOoVh4cI4zz9fwpQpbdl8moKCDiIiIiIiItKPustESCRifPvblWyz\njcf69TFaWrKTkrBypVId+oOCDiIiIiIiItJvFiwoCU2pSK2lJcaaNV0HBQYM8Bg6tOO/IUM86uvh\nj3/svibR8OFaIrM/KOggIiIiIiIi/SbdDIPDD29h330TWwUWguBCZ6tOeB68+GJpl4GNmpoEkydr\nakV/UNBBRERERERE+o3npZdhcOaZLb2quRCLwezZTSlrRgDE4x6zZjWpkGQ/0QIhIiIiIiIi0i+e\neKKE88+v6na7vmYi1Na2MmdOIzU1HZeFrqlJbClSKf1DmQ4iIiIiIiKSVYkEXHVVOVdfXY7nxYjF\nXLaD52UvE6G2tpXp01t54YVSNm2qYvDgBiZNalWGQz9T0EFERERERESyZt06OPPMKp54wg0/t9su\nwc03N7JxY4xLL61g4cL2BPyamgSzZjVlLBMhFoOpUxMMHQrr1iVoVYJDv1PQQURERERERLLijTfi\nfOMbVSxe7AILn/tcG3PmNDBqlMt0UCZC4VPQQURERERERDLu3ntLOe+8ShobXRTh1FObufzyJioq\n2rdRJkLhU9BBREREREREMqapCS68sII77ywHoLLS48orG/nqVxVRKEYKOoiIiIiIiEhGLF0aY+bM\nKl55pQSAsWMT3HZbAxMnJrq5pxQqLZkpIiIiIiIiffbMMyV84QsDtgQcDjuslSee2KyAQ5FT0EFE\nRERERER6LZGAX/2qnBNOqOLjj+PEYh7nndfE73/fwJAhue6d5JqmV4iIiIiIiEivbNgAZ51VyaOP\nlgEwZIjHjTc28PnPt+W4ZxIVCjqIiIiIiIhIj739tlsOc+FCl0A/cWIbt97awE47eTnumUSJgg4i\nIiIiIiLSKc+D+fPjbNwIgwfH2WefBA8+WMq551ZSX++WwzzxxBZ+9rNGqqpy3FmJHAUdRERERERE\n8lyqwEAs1vd26+pKueSSChYtCsoBVlFd7bFhg2u8vNzjpz9t4uSTWzLyeFJ4FHQQERERIXsn7CIi\n2ZYqMDBuXILZs5uorW3tU7szZ1aSSHQ8GAYBh223TXDPPQ3stZdWp5DOafUKERERKXp1daVMnjyQ\nGTOqOPFEmDGjismTB1JXp+szIhJtQWCgPeDgLFoUZ+bMyl4fx1paYPbsiq0CDmGDBsGeeyrgIF3T\nN6mIiIgUtc6u5AUn7HPmNPbpSqGISLZ4HlxySeeBgUQixgUXVNDUBJs3x9i0CTZujLFpU4zNm2HT\nppj/u/utn8qOAAAgAElEQVS/++f+39jYfarX4sVxnn++hClTtFKFdE5BBxERESla6ZywX3ppBdOn\nt2qqhYhEzoIFJVtlOCRbtSrOaadlr7rjypU6OErXFHQQERGRopXOCfvChbqSJyLR1NMBfzzuMWgQ\nDBrkMWiQx+DBMHCg5/8Ogwe3/3/1arjllopu2xw+XMtjStcUdBAREZGismmTCzY8+2wpc+emdyqk\nK3kiEkXpDvhvv72eadPaGDCAtLO2PA8ef7ysy8BsTU2CyZMVkJWuKeggIiIieaM3K0w0N8PLL5fw\nzDMlzJtXwssvl9Da2rMggq7kiUgUTZnSxrhxiW4DA0ce2dbjKWKxGMye3ZSy5g24rIlZs5o09Uy6\npaCDiIiI5IV0l4RLJOCtt+I8+2wJ8+aVsmBBCfX1W58VDxzosd9+bbz8cpy1a3UlT0TyT7YDA7W1\nrcyZ08ill1awcGH7cbKmJsGsWX1bjlOKh4IOIiIiEnndrTDxk580Eo/HmDevhH/+syRlEKGszGOf\nfdo48MA2Djywlb32SlBW1nnbjseFF+pKnohEV21tK5dc0sRFF1V2uD1TgYHa2lamT2/lhRdK2bSp\nisGDG5g0ScV1JX0KOoiIiEikpbck3NaV2WMxj4kTE1uCDJMntzFw4Nb37+xKnt8Kb78d5+ijM/BE\nRESyZPz4xJb/X3017LZbZgMDsRhMnZpg6FBYty5BqxIcpAcUdBAREZFIS2eFicDOOyc46KBWDjyw\njf33b2XbbdN7jOQreQMGNPCTn5SxYEEp115bzkEHtTF1qqZYiEg0rVjRfoz81regrU2BAYkOBR1E\nREQk0tJdOeJnP2vkm99s6fXjJF/Ju/HGRg4+eCDr18c444xK/vGPzQwZ0uvmRUSyZvlyd5wcNMij\nujrGunU57pBISHqXDURERERyJN2VI/bYI9H9Rj0wapTHNdc0ArB8eZxzz63E0yIWIhJBK1a4oMPI\nkTpISfQo6CAiIiKRFiwJ15VsrTBx1FGtnHRSMwAPPVTGPfcoSVREomf5cjesU9BBokhBBxEREYm0\nYEk4SH0yne214i+7rIlddnFBjx/9qJL//Ecl20UkWtozHTKb8SWSCQo6iIiISOTtt18r8RRnLTU1\nCebMaczqWvGDBsFNNzVQVuZRXx/jtNOqaG7O2sOJiPRYUEhyxAhlOkj0KOggIiIikffYY6Vblsz8\n9a+buPdeqKtrYMGCzVkNOAQ++9kEP/pREwCvv17CT39akfXHFBFJx6ZNsH69Oz6OGqWgg0SPgg4i\nIiISeXPnlgEwblyCk05q5YQTYL/9ElmbUpHK6ae3cNBBLsBx/fXlPPNMSf89uIhIJ8Ir/Kimg0SR\ngg4iIiISaRs3smWAP2NGS78GGsLicbj++ka2287NmT7rrErWrFF9BxHJraCIJCjoINGkoIOIiIhE\n2uOPl9Lc7Ab3M2ZkfypFV4YN87j2WreM5qpVcc45R8toikhuBUUkAUaMUCFJiR4FHURERCTS5s51\ny1SOGpVgr71yf0J9xBFtfOMbrpLkY4+VctttZTnukYgUs6CIZEWFx7bb5rgzIiko6CAiIiKRtXkz\nPPWUCzrMmNGas6kVyS6+uAlj2vz/V/DOOzqlEpHcWL7cHRhHjPAic4wUCdM3pIiIiETWU0+V0tDg\nzqL7Y5WKdFVVwU03NVJR4dHYGOO00yppaMh1r0SkGAWZDiNH5j4TTCQVBR1EREQksoKpFTvumGDf\nfdty3JuOJkxIMHu2W0bznXdKuOwyLaMpIv0vyHQYPlwFZiSaFHQQERGRSGpsdEUkAaZPbyUewbOW\nmTNbOOwwl4Hxu9+V8/e/axlNEelfQSFJZTpIVEXw61tERETELZO5eXM0Vq3oTCwGv/pVIzvs4E72\n/+d/Klm1SpOqRaR/NDXBmjXB9AplOkg0KeggIiIikTR3rlsVYtttE0ydGq2pFWE77OBx3XVuGc01\na+KcfXYliQK64Oh5MH9+nHvvdT+1RKhIdKxcGV4uUx9OiSYFHURERCRyWlrccpQARxzRSmlpjjvU\njUMPbeM733HLaP7jH6XcckthLKNZV1fK5MkDmTGjihNPhBkzqpg8eSB1dRF/Q0SKRFBEEjS9QqJL\nQQcRERGJnOeeK+GTT6I9tSLZj3/cxIQJLiPjsssqeOON/D7NqqsrZebMShYt6vg8Fi2KM3NmpQIP\nIhEQ1HMAZTpIdOX3t6GIiIgUpGDViupqjwMPjO7UirCKCrj55kaqqjxaWtwymps357pXveN5cMkl\nFSQSqetTJBIxLr20QlMtRHIsWLmipMRjhx30gZRoUtBBREREIqWtDR55xAUdvvjFViryaCXKT30q\nwWWXuWU033uvhFmz8qjzIQsWlGyV4ZBs4cI4zz+v1TpEcimYXjF8uEeJPo4SUQo6iIiISKQ8/3zJ\nlmrs+TK1IuxrX2th+vQWAO66q3xL1kY+CRen68ojj5RSX5/lzohIp4JMB02tkChT0EFEREQiJRik\nDxjgccgh+Rd0iMXgmmsaGTHCFXX73vcqtwwM8sXw4ekNYG68sZzddx/E179eyf33l/LJJ1numIh0\nEGQ6BMcbkShS0EFEREQiI5FoDzocdlgrVVU57lAvbbstXH99I7GYxyefxDjjjErmzcufZSenTGlj\n3LiuBzHxuHsSDQ0xHn64jLPOqmKPPQZx3HFV3HprWYcCdyKSHcHnbOTIiB9UpKgp6CAiIiKR8dJL\ncVauzN+pFWEHHNDGd7/rltGcP7+UL30pf5adjMVg9uymLYGFZPG4x29/28hf/1rPd77TzJgxLkDR\n2hrj2WdLueCCSj772UEceeQAfv3rct5/v/MAhOe5QEy+BGREoqK1FVatCqZXKNNBoktBBxEREYmM\nuXPLAKio8DjssPwOOgBMnJgAth5F58Oyk7W1rcyZ08jQoR0HMzU1CebMaeSoo1rZb782LrusiRdf\n3MyTT27me99rYvfd21cbeemlEi6/vIL99hvEgQcO4Kc/Lee119oDC3V1pUyePJAZM/InICMSFatX\nx2hrU6aDRJ+O6CIiIhIJnseWweYhh7QyaFCOO9RHngeXX14BdL3s5PTprcQiOhOhtraVJ54o4Q9/\nKGfECPjd7xqYNGnr/sZiLsAycWIzF1zQzAcfxHj44VIeeaSMF1+M43kxrC3B2hKuvbaC0aMT7LZb\nG089VbrVspxBQGbOnEZqa3MbeGpubuatt97ocpuSkjjV1VVs2NBAW1vqq80TJkykvLw8G12UIhau\nFZNuHRaRXFDQQURERCLhjTfiLF5cGFMroGfLTk6Z0tbldrm0ZIl7DhMnwn77JWhN463ZeWePs85q\n4ayzWli1Ksajj5by8MOlPPdcCS0tMZYujbN0aeevTVQCMm+99QaH33AI7NiHRj6Cx854mr322jtj\n/RKB9iKSACNHanqFRJeCDiIiIhIJQQHJsjKPww/P/6BDustOprtdrgTBgZ126t39hw3zOPXUFk49\ntYX16+GJJ0q5664y5s/v+jQ0MgGZHYFRue2CSCrhYq3KdJAoU9BBREREcs7z2oMOBx7Yxjbb5LhD\nGZDuICDKg4VEApYtcwObceP63t4228Cxx7YSj9Nt0AGiH5ARyaXly11AcIcdEmj2jkSZCkmKiIhI\nzlkb5z//KQEKY2oFpLfsZE1NgsmTozu1YvXqGE1NbuDf20yHVAohICOSa1ouU/KFgg4iIiKSc0GW\nQzzuccQRhRF0SGfZyVmzmiJbRBJgyZL2zmUy6JBOQGbs2GgHZERyLQg6aLlMiToFHURERCTnHnrI\nBR2mTm1j++0L56pdsOxkTU3HQcHIkYlIrM7QnXCxx0xMrwh0F5BxPDZuzNxjihSaYHrFiBGFc8yU\nwqSgg4iIiOTUBx/EeOcdN7Ui6oPw3qitbWXBgs3cdlvjlttmzWrKi+carCZSWuoxYkRm2+4sILPN\nNgn/sUs4+eQqGhoy+7gihcDzNL1C8oeCDiIiIpJTc+eWbfl/PgzEeyMWgxkz2ijzn2pXy0VGydKl\nblAzapRHSUnm2w8CMnPnNnDvvVBX14C1m/na15oBWLCglG99q4qWlsw/tkg++/jjGM3Nml4h+SE/\nvvFERESkYAX1HPbdt7WgCweWlLTXRfjwwwgXcggJgiNjx2bvfYnFYOrUBCecAPvtlyAehyuvbOLo\no12k4e9/L+XssytJaFwlskV4uUxNr5CoU9BBREREcmbJkhivvlpYq1Z0JaiLsGRJfpyCBYUkR4/u\n3xF/SQnccEMjBx/s9okHHyzjwgsr8DS2EgE6Bh1GjlRETqItP77xREREpCDV1ZVu+X+hTq0IC4IO\nQa2EKPO89uDImDH9P9ovL4fbbmtg0iS3gsWcOeVceWV5v/dDJIqCIpKgpWUl+qL/jSciIiIFK5ha\nseeebTkZ2Pa3mhr3c+nSWOSnC6xbB/X17mpqNqdXdGXgQLj77np2390FHq6+uoKbby7r5l4ihS/I\ndBgyxGPgwBx3RqQbCjqIiIhITqxaFeOFF4pnagW0Zzo0N8dYtSradR3CU0DGjMldhGTIELj//gZ2\n2sn14aKLKrn33tJu7iVS2NqXy4x49FIEiMQR2xjzQ+DLwG5AAzAfON9a+27SdpcC3wKGAP8ETrfW\n/qefuysiIiIZUFdXiue5gfeMGcWxPEGQ6QBuisWIEW2560w3OgYdcpuFMmyYxwMP1HPUUQNYtSrO\nOedUUl3dyPTpxRGsEkkWZDqoiGThMsacCXwfGA68BpxtrX2hi+1PAn4A7AqsBx4BfmCtXdsP3e1S\nVDIdDgSuAyYDhwFlwOPGmKpgA2PM+cBZwLeBfYHNwGPGGE3uExERyUNBPYfdd29j552L48Q5yHQA\nWLw42pkOwXKZ8bjHyJG5f3/GjfO4//4GhgzxaGuL8e1vVzJvXhbW8RTJA0HQQUUkC5Mx5gTgamA2\nsBcu6PCYMWb7TrbfH7gD+C2wB3Acbsx8S790uBuRCDpYa6dba++y1r5jrX0D+DowFtg7tNn/AJdZ\na+daa98ETgFGAsf0e4dFRESkT9asifHPfxbX1AqA4cOhstIN4KO+gkXQv+HDPcojcoln990T3H13\nPQMGeDQ3xzjllCpeeSXar6NIpnkeLFsWTK/IfUBQsuIc4GZr7Z3W2v8DTgPqgW92sv0UYKG19npr\n7YfW2vnAzbjAQ85F9Sg9BPCAtQDGmBpcWsmTwQbW2g3A88B+ueigiIiI9N6jj5aSSARTK4on6BCL\ntU9VCJajjKpcLZfZnUmTEtxxRwPl5R6bN8c48cQq3n03qqe0Ipm3cWN7kdcoZCFJZhljynAX38Nj\nXw94gs7Hvv8CxhhjjvTbGAYcD9Rlt7fpidwR2hgTA34JPGetfdu/eTguCLEqafNV/t9EREQkjwSr\nVowf38Zuu0VrUJttY8e65xv1ZTOXLs3dcpndmTatjZtuaiQe91i7Ns7xx1dFPogjkikrVrQfO1RI\nsiBtD5TQg7Gvn9lwMnCfMaYZWAGsw5UnyLlIFJJMcgNuHsr+mW44Ho8Rj3f+hVRSEu/wM5Pyte1s\nt6++56b9fG072+2r77lpP1/bznb7fW07E30qKYlTWtrzdrrr+/r1bJmLf/TRbZSV9ewxovy6p9P2\nTju535cs6d3r2137mep7ML1ip528SH6WjjkmwaZNzXz3uxWsWBHnK18ZQF1dAzvu2Pe2k+/bV9n6\nLPVFFN/TKLSd7fYz0faqVe21TEaPpsO+FfW+56LtbLef7b6nwxizB/Ar4GLgcWAEcBVuisW3ctYx\nX6SCDsaY3wDTgQOttStCf1oJxIBhdIz4DANeSbf9bbcdSCzWfRS8urqq2216K1/bznb76ntu2s/X\ntrPdvvqem/bzte1st9/btjPRp+rqKoYO7f0C8J31Ye5caPEXqzjppHKGDu1dwYAovu7pMMadfi1d\nGqe6eiAlGa6FmIm+b9jggkMAxpRTXZ25trvS0/bPPhuam+H734f334/z1a8O5Omn3TKbfW27t/fp\nrJ1sfJYyIWrvaVTaznb7fWk7+GwCTJgwIGP7e7ryte1st5/BttcAbbixbtgw3Lg4lQuAf1prr/F/\nf9MYcwYwzxhzobU2OWuiX0Um6OAHHL4ETLPWLg7/zVq70BizEvg88Lq/fTVutYvr032MtWs3d5vp\nUF1dxYYNDbS1ZTZVKV/bznb76ntu2s/XtrPdvvqem/bzte1st9/XtjdsaNgyUOytDRsaWLduc4/v\n113f7723Aihl7NgE48Y1sG5dZtvvi/5oe8cdm4FyWlvh7bfrGT06M9MXMtn3t9+OAQMA2G67RjZs\n8CL7WfrmN2HZsjKuvbacV1+FI49s449/bGTAgL63vWFDQ4+276qdbHyW+qKYj4+5bD8Tbb/3XhlQ\nzsCBHolEfYdjaNT7nou2s91+Om33JOhorW0xxryEG/v+DbaUIPg88OtO7jYAaE66LYErUZDzuWeR\nCDoYY24ATgSOBjb7hS8A1ltrG/3//xL4sTHmP8Ai4DJgKfDXdB8nkfBIJLr/Ym9rS9Damp35Ufna\ndrbbV99z036+tp3t9tX33LSfr21nu/3etp2Jk6q+Pq9U99+0CZ56yl3ar61t7VM/o/i6p2P06LYt\n///gAxg+PLOPk4m+L1zYnn4xcmQrbW2xjLXdld62f8EFTXz8Mdx5ZzkLFpRw6qkVfrHJvrWdqcFJ\nNj5LmRLV9zTXbWe7/b60vWyZ+zl8uNfpPhrVvuey7Wy3n+G2rwFu94MP/8atZjEAuB3AGPNTYKS1\n9lR/+4eAW4wxpwGP4VZ5vBZ43lrbWXZEv4lKBaPTgGrgH8Dy0L+vBBtYa68ErsPNS3keqAKOtNYm\nR3REREQkop58spTGxmDVipYc9yY3dtqp/aR08eKcX4BKKSgiCTBqVPQKSSaLxeDnP2/imGPcPvXk\nk6WcfXYlra0wf36ce+91P73oPxWRbgWFJEeOVBHJQmWtvR/4PnAprpzAZ4DDrbWr/U2GA2NC298B\nfA84E3gDuA94Bzi2H7vdqUhkOlhr0wp+WGsvxhXHEBERkTwUrFoxfHiCvfcuzhPm7baDAQM86utj\nkV3BIigiucMOCaqyO8U6Y0pK4De/aWTDhhhPPVXKn/9cxhNPlLJxYxDYqWLcuASzZzdRW1s8y7RK\n4Vm+3O3TI0YoilbIrLU34BZZSPW3b6S47Xp6UHqgP0Xzm05EREQKTkMD/P3vLuhQW9tKvEjPQmKx\n9mUzg8F91ATLT0ZxucyulJfDrbc2MH68m8LSHnBwFi2KM3NmJXV1kbjuJtIrynSQfBPNbzoREREp\nOE8/XUp9vRsEHnVUcV9pDgbzUZ9eMXp0/g1qqqqgubnz1zWRiHHppRWaaiF5qaEB1q1z+/fw4dqJ\nJT8o6CAiIiL9Iphasf32CSZPbutm68KmTIfsWbCgpNtpKwsXxnn++QyvVSrSD1asaA+oKdNB8kU0\nv+lERESkoDQ3w+OPu6DDkUe2UlLk470xY9xgYfnyGC0Rq6dZXw9r1uRvpsPKlellj6S7nUiUBFMr\nAEaOzL+goBQnBR1EREQk6+bNK2HDhmDViuKeWgEwdqwbLCQSMZYti9bgd9my9tPDIDiST9JNOVdq\nuuSjoIgkqJCk5A8FHURERCTrgqkVQ4Z4HHBAcU+tgPbpFRC9KRbB1ArIz+kVU6a0MW5c18GSmhpN\n8ZH8FGQ6lJd7bLdd/n0+pThF61tORERECk5rKzzyiAs6HH54K2VlOe5QBISDDlFbNjMcBMnHTIdY\nDGbPbiIeTz0gi8c9Zs1qIhatBBORtAQ1HYYP94p2BSDJP9pVRUREJKv+9a8S1q51pxwzZkSsgEGO\nbLMNDB7sBsXhzIIoWLrU9WfIEI9Bg3LcmV6qrW1lzpxGamo6Bk1qahLMmdNIba2m+Eh+CqZXjBiR\nfwFBKV4KOoiIiEhWBVMrBg70mDZNKe3grsYHWQQffhit07Eg0yEfsxzCamtbWbBgMyee6AJdVVUe\n//rXZgUcJK8F0ytURFLySbS+5URERKSgJBJQV+eCDl/8YiuVlTnuUIS0L5sZrUyHIOiQjytXJIvF\nYMoU9zwaGmJs2pTjDon0UXumg4IOkj8UdBAREZGs+fe/S/joo2Bqha4whwUrWEStpkMwvSLoX74L\nXxFevjxar7VIT7S0wOrVml4h+UdHXhEREcmaIMuhqsrj0EMVdAgLMh1WrozT1JTjzviam2HlSjeo\nKYRMB4CRI9ufR3i5QZF8s2pVDM9z+7CmV0g+Kc11B6SwNTc389Zbb3T695KSONXVVWzY0EBbW+cn\nNxMmTKS8vDwbXRQRkSzxvPagw6GHtjJwYI47FDHh5SiXLo2xyy65H0QsW9Y+qBk9Ovf9yYRRo5Iz\nHVRXRPJTOGimTAfJJwo6SFa99dYbLF9+CBMmdL1ddXVXbQA8zV577Z3JromISJa98kqcpUs1taIz\nyctm7rJL7gfDwfsFHfuXz6qrYfBg2LhRmQ6S34IikqBMB8kvCjpI1k2YAPvs07c21q3LTF9ERKT/\nPPRQCQDl5R5f/KKCDsnCg3pXvDEKQYf2QXmhTK8AGD0a3nlHQQfJb8H+G4977Lijgg6SP1TTQURE\nRDLO8+Chh9y1jWnT2hg8OMcdiqDBg2Ho0KCYZDQGw0FRy4EDPYYMyXFnMmjMGPdThSQlnwWZDjvu\n6FGqS8eSR3TkFRERkYx74w344INgakVLjnsTXWPGBMtmRuOULJheMXZsglg04iAZMXq0+7liRQE9\nKSk6wf6rqRWSb6LxDSciIiIF5U9/cj9LSjwOP1xTKzoTTLGIyrKZwfSKQikiGQiCDsuWReN1FumN\nIFNHRSQl3+jIKyIiIhnjeTB/fpxbb3W/779/G9tum9s+RVmwgkVUplcEGReFVM8B2qdXbNoUY+PG\n3PZFpLeU6SD5SkEHERERyYi6ulImTx7IjBlVLF3qbnvrrfiWZTNla0Gmw+rVcerrc9uXtrb2QnXB\ntI9CEWQ6gOo6SH5KJGDlSvf5HD5cQQfJLzrqioiISJ/V1ZUyc2YlixZ1PLX4+OM4M2dWKvDQifAK\nFuHlKnNh5coYra1B0KGwBjXhoMOyZdHIKhHpidWr2z+fI0cWVlBQCp+CDiIiItInngeXXFJBIpF6\nMJdIxLj00gq8whrHZkR4cJ/rKRbhYpaFOr0C2lcAEMkn4SKoml4h+UZHXREREemTBQtKtspwSLZw\nYZznny/ppx7lj/A0hlwXk1yypH1QU2iZDtXVMGiQe07BFBKRfBKeFqRCkpJvFHQQERGRPgnmGWdq\nu2IycCBsv300VrAIpndUVnrssENhBR1iMRgxQkEHyV/hTAfVdJB8o6CDiIiI9MnmzeltpxPl1MaO\nda9LONMgF4LHHzXKI1aA4/JRo4Kgg05/Jf8EQYfttktQWZnjzoj0kI66IiIi0msPPVTKj37U/Rlw\nTU2CyZPb+qFH+SeYYpHrTIegpkOhrVwRCIrvha8Yi+SLIFgWZOyI5BMFHURERKTHPA+uvrqcmTOr\naGyMUVrqEYulPhmOxz1mzWoqyKvnmRCsYJHrTIdgekXhBh3c/rlsmU5/Jf8EwTIVkZR8pKOuiIiI\n9EhDA5x2WiU//3kFADvumGDu3HpuvbWRmpqOA9aamgRz5jRSW9uai67mhaBo49q1cTZtyk0fEglY\nutQNakaPLsxBTTC9YuPGGBs35rgzIj0UZDoMH16YQUEpbFo0W0RERNK2alWMU06p4pVX3EoUEye2\ncdddDf7VtwTTp7fywgulbNpUxeDBDUya1KoMh24EmQ7gpljssUf/DypWr47R1OTeqELPdAC3bObg\nwYX5PKXweF57IV5lOkg+UtBBRERE0vL663G+9rUqVqxwV9xmzGjhuusaGTiwfZtYDKZOTTB0KKxb\nl6BVCQ7dCgcdliyJscce/d+HIMsBCjnTof11XrYsxqc+lcPOiPTAJ59AQ0MQdFCwTPKPpleIiIhI\ntx56qJSjjhqwJeDwve818bvfdQw4SO+EB/m5KiYZFJGEws10CKZXgIpJSn4Jr7iiQpKSjxR0EBER\nkU55HlxzjSsY2dAQo6LC48YbG7jggmbiOovIiMpKGDYstytYBEGH0lKvYJc2ra6GAQO0bKbkn3CQ\nTNMrJB/piCsiIiIpNTXFOf30Sn72s/aCkX/5Sz3HHqs5E5kWFJNcvDg3V+CD6RUjR3qUlOSkC1kX\ni7Wnpi9frkwHyR9BhhnAiBGFmYkkhU1BBxEREdnKmjXD+f739+TBB8sA+PSn23jssXr23lsnvNnQ\nvmxmbjMdCnVqRSC4SqxMB8knQZBs8GCPQYNy3BmRXtARV0RERDp4+eW9+PrXX+Ddd6sBqK1t4aGH\n6jvMiZfMCoIOuZpeEWQ6BBkXhSoIOqimg+STYH9VEUnJVwo6iIiIyBZ/+tN/ccABz/HRR6MBOOec\nJubMUcHIbBs71g2GN2yIsX59/z6257VnOoweXdiDmmDQtmyZToElfwSZOSoiKflKR1wRERHB8+Dy\nyy/kuOP+REPDAMrLGzn//Lf54Q9VMLI/hKc19He2w7p1sHlzkOlQ6EGH9uDOpk057oxImoJMBwUd\nJF/pNEJERKTIeB48++yB3HvvCTz77IHU11dy0kl/4KKLLgdg2LCV3HTTNA499KMc97R4BNMroP+D\nDkuXhpfLLOxBTTg9PVycTyTKgn1VRSQlX5XmugMiIiLSf/7852P4wQ9+wfvvj99yW0VFI01NlQDs\nuecr/O1vR7Ny5VLWrctVL4vPqFEesZiH58VYsqR/6w2Ei1cW/vSK9qDKsmUxdt01h50RScOmTS4z\nB7RcpuQvBR1ERESKxJ//fAzHHfdHEomOayIGAYfJk//Fk08exsCB9axcmYseFq/ycjegWLYs1u+Z\nDkGQIxbzCn5Q0zHTQcUkJfrCGTkqJCn5SnllIiIiRcDz4Ac/+MVWAYewjz/engED6vuxVxIW1FPo\n7yuR0EwAACAASURBVGUzg+kVI0Z4lJf360P3u222gQEDtGym5I9guUyA4cMLOygohUtHWxERkSIw\nb96BHaZUpPKf/+zKc88d0E89kmTBChaLF/f39Ar3eIU+tQIgFmu/WhwezIlEVTgjR5kOkq8UdBAR\nESkCr7322bS2W758ZJZ7Ip0JMh0WL47j9eMFzfblMovjKmqwAoAyHSQfBNMrKis9hg7NcWdEeklH\nWxERkQK2bNlIzjjjes4555q0th85cnmWeySdCVaw2Lw5xtq1/XcVPpheEV5Bo5AFdSuU6SD5INhP\nR4zwiGmXlTylQpIiIiIF6JNPyrj99qt58MEzthSKBA/o/Kx1/Pj3OOCA5/qlf7K1YHoFuCkP222X\n/cyDjRvhk0+C6RXFkekwalQwvULX3iT6gkwHTa2QfKajrYiISAFZtw6uuKKcU0+dwj33fI+mpkpi\nsQRf+9qdXH/9GcTjbSnvF4+3ceWV5+lKWg4F0yuAflvBopiWywwE0yvWr4+xaVOOOyPSjaCmg4pI\nSj5TpoOIiEgB2LgRbr65nBtvLGfjxvbIwfHH38/FF1/MHnu8A8CIESs577wr+c9/dt2yzfjx73Hl\nlefx5S//pd/7Le1GjvQoKfFoa4v1WzHJpUvbH6d4ple0P8+VK2OMH6/BnERXEHRQpoPkMwUdRERE\n8tjmzXDrreX85jflrFvXPoCcMmUNZ511GCed9FqH7b/85b9wzDF/Yd68A1mxYgQjRy7ngAOeU4ZD\nBJSWwqhRHosXx3KS6TBqVHEMvoOaDgDLlsUZPz519o9IrjU2wpo1wfSK4vh8SmFS0EFERCQPNTbC\nXXeV8ctflrN6dfvAcdq0Vi64oIl4/E2GDn0t5X1jMTjooHn91VXpgbFjEyxeHO8QDMim4HG23z5B\nVVW/PGTOha8Yh5cjFImalSvb989gWpBIPupR0MEYUwncD1xlrX02O10SEREpbp4H8+fH2bgRBg+O\ns88+iS2ZCC0tcM89ZVxzTXmHQniTJ7fywx82M3Wqu2r7yiu56Ln01ZgxbmCxZEn/Tq8IF7EsdEOG\nQFWVR0NDTMUkJdKCIpIAI0ZoeoXkrx4FHay1jcaYacC1WeqPiIhIUaurK+WSSypYtCg42axi3LgE\nF13UREMD/OIXFXz4YfuJ6F57tXHBBU0cfHCbpkgUgKCuwpIlcTyPrL+nwXKZxVJEEtxrOnKkx/vv\nx1i2TB8aia5wJo6mV0g+6830iseBLwJPZ7gvIiIiRa2urpSZMytJJDoOhBYtijNzZiXh5S732MMF\nGw4/XMGGQhKsYNHQEGP16hg77pjdgUZQsLJYlssMjByZ4P334x2uJItEzfLl7vNZWuqx/fbF9RmV\nwtKboMNtwM3GmMHAw8Aq3MLfW1hrX85A30RERIqG58Ell1RsFXBo527fZZc2LrigmaOOaiWu8VLB\nCU9zWLw4u0GHhob2InXh5TqLQTA/PhjUiURREBQbPtyjpCTHnRHpg94EHeb6P8/w/4W/DWP+7/pY\niIiI9MCCBSWhKRWdu+qqJvbfX9X2C1V42colS+JMmpS9YEB4akGxBR1GjXLPVzUdJMqCoNjw4cpy\nkPzWm6DDIRnvhYiISJELVynvyurVujJbyIYN8ygr82hpyf6ymeH2i216RZDp8MknMTZvhoEDc9wh\nkRRWrgyWyyyuoKAUnh4HHay1z2SjIyIiIsUs3StZuuJV2EpKXABg4cLYlnoL2RIUkYTiy3QID+JW\nroyxyy76XEn0BJkOWi5T8l1vMh0AMMbsDkwCxgC3WmtXGmPGA6ustRsz1UEREZFiMGVKG+PGJbqc\nYlFTk2DyZE2tKHRjxiRYuDCe9UyHYLnMIUM8Bg/O6kNFTnglgGXL4uyyiz5XEi2trbBqlfuMKtNB\n8l2Pv82MMQOMMXcDbwK3ApcBI/0//xS4KHPdExERKQ6xGMye3UQ8nvqKVjzuMWtWk1aqKAI77dS+\nbGY2BUGNYlouMxAexKmYpETRRx/FthQW1nKZku968212FXAocCRQTXj9LreaxREZ6JeIiEjRqa1t\nZc6cRsrKOp5g1tQkmDOnkdra1hz1TPrTmDHu/V+6NEYii/GAINOh2KZWAAwdCpWV7nXWspkSReFg\nmKbVSb7rzVH2OOB8a+3jQHPS3xYB4/rYJxERkaI1bVorLS3u/yefDHV1DSxYsFkBhyISrGDR3Bzb\nkl6dDUEmRRDkKCaxWPvV4/AqHiJREQ6GaXqF5LveBB0GASs6+Ztq/4qIiPTBm2+WECQRzpwJ++2X\n0JSKIhPOPPjww+xchW9ubl8xpRinV0D7QE6ZDhJFK1a4z2cs5jFsWPEFBqWw9OYo+zpwbCd/qwVe\n7H13REREitvrr7d/NX/ucznsiOTM2LHtA4wlS7ITcVq+PIbnBdMrinNAE6wIoJoOEkXLl7vvgh12\n8Cgvz3FnRPqoN6tXXAb81RgzAHgA8IB9jTEnAt8EpmewfyIiIkXl1VdLABg/PkF1dZx163LcIel3\nO+7oUVnp0dgYy1oxyXC7xVjTAWDUKPe8g8GdSJQEmQ5aLlMKQY+PstbaOuCrwAHAX3A5oDcAJwAn\nWWufzGgPRUREikiQ6bDnnsU5EBRXbyAIBCxenJ2r8EERSSje6RXBYG7duhj19TnujEiS9qBDcX4+\npbD0JtMBa+0fgT8aYz4FbA+stdb+X0Z7JiIiUmQ2bYL33nNBh89+to1efk1LARgzxuO997K3bGbQ\n7sCBHkOHZuUhIi9cnG/lyhg776wryhIdQQaOlsuUQtDjsxljzBeAJ6y1nrX2XeDdzHdLRESk+Lz5\nZsmWefbKdChuQaZDtgpJtq9cUbyFSsODuWXL4uy8c1sOeyPSLpFoL/SqoIMUgt58kz0GLDfG/MoY\nMyXTHRIRESlWr73mvpZjMY+JExV0KGZBMcnly2O0ZmG11GB6xejRxTugCQ/mVExSouTjj2M0N7t9\ncvhwfRdI/utN0OEzwK24lSrmG2M+MMZcYYyZmNmuiYiIFJegiOQuuySors5xZySnxo51A43W1tiW\nud2ZFM50KFbbbusKdoKKSUq0BFkOoEwHKQw9nl5hrX0TuBC40BizL3AicCpwgTHmbeBua+1PM9tN\nERGRwtLc3Mxbb73R4bZ//3sfoIyxY9fw8suW6uoqNmz4/+ydeXxU9bn/32cmK0sgyBbCFkC/QJRF\nQdzQgrW2ohVbWtvbazfuT21ttVbB22qlUG9toVZrXeu1tbXe2pYWxOJSrVRBQQHZZDksAgES9kBY\nEpLMnN8f3zmZSTJJZk7O5MzyvF+veWXmzDmf8+Q7Z86c73OepZpAIPrEsLT0PHKkl1rSEO0zjcTv\n97X5mYL+XAcODE+C9+zxMWCAe6H/gUD4zn4mRzoYhi4muXOnIZEOQlIReTxG1h4RhFSlXRWqTNP8\nAPhAKfV94FrgSeABQJwOgiAIgtAKGzduoLx8EqWl+vWpU13Yu/c4AKNG/YyCgkcAWox42LgRYAlj\nx16QeGOFmNi4cQNXPzEJerdD5CC8/u0lDBgwrmFRWZnBJZe03z6b/fsN6uv1pCaTIx1AT+h27vRR\nUSGRDkLyEBl507dv5joGhfShXU4HpVQucB26heY1Ib1/umCXIAiCIKQ9paUwfrx+/s47Y7EsfaH5\nuc+taljeGpWVCTROcEZvoLj9MmedZdGpk8Xp0wZlZe5OiCM7YmS608Fum7lvn0Q6CMmDnVJVWGjR\nqZPHxgiCCzjpXuEHrkanVXwW6AK8C9wF/NU0zcOuWigIgiAIGcCqVfrOtmEEGTt2jcfWCF5jGLqu\nw5Yt/gQ4HcIT7ExOrwAoLtZOl0TUzRAEp9iRDlJEUkgXnEQ6HAS6A2uBnwAvmqa511WrBEEQBCHD\nWL1ap0koZdKlyymPrRGSgYEDLbZsaewkcIO9e/WEJjfXolevzHY62JEOR4/6qK6G/HyPDRIEwk4w\nKSIppAtOnA6PAn8yTXOr28YIgiAIQqZiOx3GjVvlsSVCsmCnPkSmQ7hBZLtMX4aXMogs0ldRYTBk\niEzyBO8JOx0k0kFID5x0r5idCEMEQRAEIVOpquqKaQ4H4IILVntsjZAs2G0zy8sN6uogO9sdXTtd\no39/mdAUF4edDOXlPoYMca9LiCA4wbLC6RV2JI4gpDqOCkkqpcYCPwQuA3oAR4GlwE9N01zrnnmC\nIAiCkP6sWTO24blEOgg2AwboCUcwaLBvn8Hgwe5MQOz0CtupkclETuqkbaaQDFRVwenT+lgUp4PQ\n0RgGPYG7gfHAAOAGy2KjYXAH8L5lscKJbtxBdUqpicDykCF/Au4P/R0PLFdKXebEEEEQBEHIVCKL\nSI4ZI757QRPpFHCrmKRlhTs1ZHoRSdBdQnJz9ThEtikUBK+IbN9aVCSOQaHjMAzOB7ahO1PuBYYC\nuaG3i4E7nWo7iXT4GfBv4FrTNOvthUqpGcDi0PvieBAEQRCEGLHrOQwfvkWKSAoNRDoddF2H9of+\nHzxoUFNjOx1kQmMY+m7yrl2GRDoISUHkcSiFJIUO5mF0cMH1gAXcFPHe+8CNToWduHTHAo9GOhwA\nTNMMoItMnu/UGEEQBEHIRKSIpBCNbt2ga1c96Sgrc2dCbBeRhHD6RqZjF+uLvMMsCF4ReRxKIUmh\ngxkPPGpZ1KGdDpEcAno7FXZydj3Vyg77hN4XBEEQBCEGjh8vYOtWBUgRSaExhhGOdnArvcKu5wDh\n7hiZjn032U47EQQvsSMdOnWy6NrVY2OETOMUUNDCewOBI06FnfyCvQz8XCn1yciFodcPAoucGiMI\ngiAImYYUkRRaw3YMuOV0sHWysiz69pVIB4iMdBCng+A9+/eH22UackgKHcvrwH2GwVkRyyzDIB+4\nA3jFqbCTmg53AaXA60qpKuAgOvKhAFiJrnYpCIIgCEIM2EUkfb6AFJEUmjFokHYM7NnjbnpFv34W\nfr8rkimP3SHgyBEfNTWQl+exQUJGI+0yBQ+5B3gXXUxyCTrF4gFgZOj5fU6F43Y6mKZZqZS6GLgW\nXTCyEN0ycxmw2DRNR7F6oa4YM4ALgCJgqmmaiyLe/x3wtSabvWaa5jVO9icIgiAIyUBkEcnOnU97\nbI2QbNiRDvv3uzMhttMrJLUiTHFxeCzKyw2GDJHJnuAddnqFFJEUlFK3oW/o9wXWAd81TXNlK+vn\nALOAr4S2KQfmmKb5XCz7syz2GQZj0F0qrgJ2AGcBLwC/tCyOOv1fnEQ6EHIsLMLdVIrOwFrgWeDv\nLazzKvB1wHb3n3Fx/4IgCILQ4UgRSaE1IjtY7NtnMHRo+yYidsSEtMsMEzm5q6jwMWRI+7uECIJT\n7EKS0i4zs1FK3Qg8BNwMfIB2BLyulDrHNM3DLWz2V6AX8A20w6CIOMspWBbH0I6LWQ5Nj4ojp0Mi\nME3zNeA1AKVUSzGEZ0zTPNRxVgmCIAhC4jh5soBt284BpIikEJ3IDhNlZT6GDnU+IbYsu/WmRDpE\nEhnGLm0zBS85fRqOHdPHoKRXZDx3Ak+bpvkHAKXUrcAU4JvA3KYrK6U+DUwEhpimeSy0uKyDbG2T\npHE6xMgnlFIHgErgLeA+0zQdh3kIgiAIgpds2RLuMi2RDkI0IiMddBFI506HY8fg1Ck9oRGnQ5ie\nPS1ycixqa42GfHpB8AK7iCRIu8xMRimVjS458FN7mWmallLqTeDiFja7DlgF3KOUugndiWIR8CPT\nNGti2a9hsJPmrTJtgsBxdGbC45bFh7Fo2qTSmfVV4KvAZGAmcAXwSitREYIgCIKQ1GzeLEUkhdbp\n2hUKC90pJmlHOYCkV0RiGOG7yhLpIHhJpNNLajpkND0BP3CgyfID6FoN0RiCjnQoBaaiu01MAx6P\nY78vhfZbCHyIzkL4MPQ6G11X4nJghWHwyZZEopEykQ6maf4l4uVGpdQGdK7KJ9DVNdvE5zPw+Vr+\nMfH7fY3+ukmqardX3y2b/H4fWVnO959p456u2onWF9u90U9V7fbq+/0+tmzR9RxGjtxEp07VjjRa\nOje68T8n47k30frJ+Js3aFCQyko/e/b4W/082rK9vDzcrqKkhLg+23T/TIuLLXbv1gU7I8dFrmOS\nUz9dbT9wIPwdHTAgvu9oLPrtJVW1E62faNtjxIeORvgP0zRPAiilvg/8VSn1bdM0Y6mFuAvYDXzG\nsjhlLzQMuqDbZW4Bbgk9nw28GatxKeN0aIppmjuVUoeBYcTodOjRozNGDA1vCwry22ld+mk71XfL\npoKCfAoLO7dr+0SRjOOe7tqJ1hfbvdFPVW2n+gUF+Q2RDk7rObR2bnTjf07mc2+i9ZPpN2/oUFi7\nFsrLsygsbPvSrSU7jhzRfw0DSks7kZPjzLZE4tVnWlIC770H+/c3HmO5jklu/XSzvbJS/83JgWHD\nOhPDtCUufbdIVe1E67uofRidS9enyfI+wP4WtqkA9tkOhxCb0Q0Y+qNv1rfFncBtkQ4HAMvipGEw\nD3jSsphrGDwJ/CEGvQYcOR2UUn5gAvofaNa8yS54kUiUUv3RLTwqYt3m6NFTbUY6FBTkU1VVTSDg\nbh5Vqmq3V7+qqpqCgvbbUFVVTWXlqbZXbEKmjnu6aidaX2z3Rj9VtdurX15ey969wwDnTofWzo1u\nnH+T8dybaP32/ua5QdNx79s3B8jm448tKitbbqvalu1btmidvn2DnDpVzak4Ptp0/0x79swGctiz\np/EYJ+ozjRWvxyVZ9dPV9o8/1t/RoqIgx445O/ZSddzT9TO1icfpaJpmnVJqNXAloW6RoZICVwKP\ntrDZu8A0pVQn0zTtk5hCRz/sjXHXPYGWrhy6odMsgPhbZ8btdFBKnY9uaTmAcOvKSCzi9HyEdDuj\noxZszSFKqdHof+ooum3H39DenWHAz4GtwOux7iMYtAgG286PCgSC1NcnpnhLqmo71XfrS93e/y3T\nxj3dtROtL7Z7o5+q2k71TTN8AeK0iGRr+3Xj/JvM595E6yfTb17//gEgm0OHDKqqgnTqFN/2NmWh\nOuYDBjgft3T9TPv21csPHzY4eTJIXl54m0TvuyO290o70frpZvve0NSwqKj9+03VcU+3z7Qd/BJ4\nLuR8sFtmdgKeA1BKPQj0M03za6H1/w+4D/idUurH6NaZc4FnY0ytAJ098DPDYJdl8Z690DC4DHgQ\n3cgBtDNjVzz/jJPEkyfRlSsno0M8Cps8ejjQBBgHrAFWox0XD6ELV8xGh5eMQhe3MIFngJXA5aZp\n1jncnyAIgiB4xtatXQFdRHL06HUeWyMkM5EdLCKLQcbL3r16Wyki2ZzIon0VFVJMUvCGigr9HZUi\nkkKonuHdwBz0HHkUcLVpmodCq/RFBwHY658CrgK6o+fJz6PnznfEsdtbgEPAUsPgiGGwxTA4AryN\nLmJ5S2i9IDoAIGacpFeUAl8wTfNtB9u2SEivtV/ST7u5P0EQBEHwkm3btNOhtHSjoyKSQuYwcGB4\nArJnj4FSznRsh4W0y2xOZHvCigofJSXOW5MKglPs7il9+4rTQQDTNJ8AnmjhvW9EWbYVuNrp/iyL\nfcAFhsE16ICAInQpg5WWxasR6z0Tr7YTp8NWWs71EARBEAQhBmyng9N6DkLm0L9/eEK8e7cPHQAa\nHydPwrFjekIzYIBMaJpit8wEaZspeENtrU7vgcZOMEHoaCyLV9AdKlzDSYzencAPlFLD3TREEARB\nEDKFY8egokJXuRang9AWnTtDz556EuI0vSJyu0gnhqDp2dMiJ0c7HsrLPW17J2QoBw4YWJZ2OkQ6\nwQTBCwyDToZBj6YPp3pOIh0eQ+eQfKSUKgeONXnfMk1ztFODBEEQBCHdWb8+3IvdaRFJIbMYONDi\n8GGdXuGEyO0k0qE5Pp8OaS8rMyTSQfCESGeXRDoIXmAYGOhilLegUyui4W9heas4cTrYhR4FQRAE\nQXDA2rX6N9vvr5cikkJMDBwY5MMP/ZSVSaRDoujXL0hZmU+cDoInRBYwlUgHwSPuBL6P7nrxP8AD\n6Hy+LwE5oWWOiNvpYJrm153uTBAEQRAEWL9eTwBLSjaSn1/jsTVCKmAXf3Qa6WB3rujZM0h+vmtm\npRV2xwBJrxC8wHZ2+XwWvXuL00HwhOnALOBxtINhoWXxoWHwE2ARMMypcLvOqkopQynVTynlJGJC\nEARBEDISO9JhxAip5yDEht3B4uhRHydPxr+97ayQ1IqWsUPaJdJB8AK7XWafPhZZMrMSvGEwsNay\nCAB16PabWBZBdBeNrzsVduR0UEpdrZRaAdQAe9B9Q1FK/UYp9RWnxgiCIAhCulNZSUOI/IgRUs9B\niI3INpdOUizsSAdpl9kydqTD4cM+zpzx2Bgh47DTK+zjUBA84AjhLpVlwPkR7/UEOjkVjvtXSyn1\nZXQLjZ3At4FId/AOoFnPUEEQBEEQNJFFJIcPl0gHITYGDox0OsR/J96OdOjfXyY0LRE52YvMrxeE\njsBO6ykqEseg4BnvAuNDz/8P+LFh8AvD4EHgl8C/nAo7Cd75EfCIaZp3KaX8wDMR721EF6AQBEEQ\n0gTLgvfe83HiBHTt6mP8+CCGXI87Zt067XTw+SyGDVvvsTVCqhDpLNBFIQMxb1tdDYcOSaRDW0R2\nDKio8DF4cOxjLAjtxXZ0SRFJwUN+DBSHnv8UnV7xZSAfeAP4rlNhJ06HIehIh2icAro5NUYQBEFI\nLhYvzmL27Fx27bID4/IZPDjIrFlnmDKl3lPbUpV16/RYDh58irw8KSIpxEZeHvTpE+TAAV/c6RX7\n9kW2yxSnQ0tETvakroPQkQQCcOCA7XSQ76jgDZaFCZih52eAO0KPduOkpsN+YHgL740Cdjs3RxAE\nQUgWFi/OYvr0vAiHg2bXLh/Tp+exeLFUunKCHelw9tknPLZESDXsYpLxplc0bpcpd1Fbolcvi+xs\nPT779kkHC6HjOHzYoL5eajoI3mIYvGUY0ef5hsE5hsFbTrWdnFH/D/ixUurKiGWWUupcYCbwR6fG\nCIIgCMmBZcHs2bkEg9EnN8GgwZw5uVhybRQXR4+GiwCK00GIFztKId5Ih0ing0Q6tIzPF452kJoO\nQkcSGVkjTgfBQz5BuJBkUwqAy50KO3E6/Bh4D53XsT+07FVgHbAK+JlTYwRBEITkYMUKf7MIh6bs\n3Onj/ff9ra4jNMaOcgBxOgjxM2iQdhhEOhFiYe9ePaHp3t2ia1fXzUor7NB2Sa8QOhK7iCRA377i\nGBQ8pSWv1yXAQaeiccfGmqZZC1yvlJoEXIVun3EUeNM0zTedGiIIgiAkD/v3x3bBHet6gsbuXJGV\nZTFkyCmPrRFSjQED9LVgVZXBsWPQvXts29lOiv79ZTLTFsXFeowjJ4GCkGgiI2v69pVIB6HjMAx+\nAPwg9NIClhgGTX8sctF+gyec7sdxQq5pmkuAJU63FwRBEJKXWC965OIoPuwiksOHB8nJkQmgEB+R\nbTP37PHRvXtsx1C4XaYcc21hp1dIpIPQkdhOh549g+TleWyMkGm8BzwEGMD9wJ+AvU3WqQU2Ay87\n3UncTgelVBnwIvAn0zTXON2xIAiCkLxcdFGAwYODraZYlJQEmTBBWsrFg51eMXq0jJsQP5H1GMrK\nfJx3XmxOhL179ffYLkQptIzdNvPQIR+1tR4bI2QMdmSNtMsUOhrL4m3gbQDDwAKesSzK3d6Pk9ix\nvwBfAlYppbYope5XSp3jsl2CIAiChxgGzJp1BsOIfgHk81ncf/8ZDLkZGDNHjhgNYe6jR8sdZyF+\niostfL74OljU1obToCTSoW0ii/hJMUmho7CPNXE6CF5iWcxOhMMBHDgdTNO82zTNgcAk4C3gNmCz\nUmq1UuoupVSx20YKgiAIHc+UKfVRJ8clJUGefbaGKVPqPbAqdbFTK0AiHQRn5OSEJyWxFpMsLzca\nutBIu8y2sSMdACoqpK6D0DGEIx3EMSh4h2HgMwxuNgz+aRhsMgw+bvLY4VS7PTUd3gHeUUp9F7gS\n+DJwH7p7RbZTXUEQBCE5sKxwLrjPZxEMGuTlWbz77imyHP96ZC6RRSRHjAiyebPHBgkpyYABQfbt\n88XcNtNOrYDGNSGE6ERGOpSXG5SUeGiMkBFYVjgaSdplCh7zc+AudLrFEnQtB1dw47LRAHIIV7WU\nWDRBEIQ0YOdOgyNH9ITl2msDLFqURU2NwfbtPoYPl8lLvNiRDiNGSKEwwTkDB1qsWBF2CLaF3S4T\nJL0iFnr1ssjKsqivN9i3zydOByHhVFZCTY2dXiHfUcFTvgLMsix+4rawo7gxpZShlLpSKfUMcABY\nBAwFfgQMcNE+QRAEwSNWrfI3PL/11rqG52vXSsixE6SIpOAGdjHJ3bt9WDHcFLUjIjp1sigsTKRl\n6YHPF05hkZoOQkcQ2Z5VIh0Ej8lDd7NwnbivHJVSjwL7gDeAi4FfAmebpjnBNM1HTNOscNlGQRAE\nwQNWrtST5F69gkyYEKRvX7187Vp/K1sJ0Th82GgIc5cikkJ7GDRIHz+nTxscPdr2pDjcuSIohV9j\nxL7bLG0zhY4g0rklhSQFj3kBuC4Rwk7SK64FnkO3zNzgrjmCIAhCsmBHOowfH8AwYNw4+Mc/xOng\nhPXrpYik4A4DBoQnJWVlBmed1fokxU6vkCKSsVNcrMcq8g60ICSKyIKlkl4heMwK4AHDoA86wOBY\n0xUsi787EY7b6WCa5hAnOxIEQRBSh5MnYfNmfSE0bpyeJI8fr50OH32k+9fn5HhpYWphp1ZkZ+si\nkoLglMhikHv2+Bg7tvXjyU6vkHoOsWPfbZZIB6EjsI+zggKLLl08NkbIdJ4P/R0E3BjlfQtwdOcp\nJqeDUqoHcMw0zWDoeauYpnnUiTGCIAhCcvDhh/6GNnvjxunJyvjx+r3aWoMtW3yMGiWTmFiJLCKZ\nm+uxMUJKU1Rk4fdbBAIGu3e3fic+EAhPaCIjJITWKS7W57ZDhwzq6sTxICQWO9Ihsl2rIHhEdiMr\n7gAAIABJREFUwkrnxhrpcAhdv+ED4DDay9EaEnsrCIKQwtipFdnZVigdwMe4ceH316zxi9MhDqSI\npOAWWVk6/L+szGizg8WBAwb19bbTQb6vsWJHOliWwZEj4iUUEovtGOzbVxyDgrdYFrsTpR2r0+Gb\nwI6I5/KtEARBSGNsp8N55wXJz9fLevXSE5c9e3ysXevja1/z0MAU4tAh3XoPpIik4A4DBwYpK/Ox\nZ0/rkQ52agVIekU8RN5xPnxYnA5CYrELSUqkg5AsGAafBsaju1I+YFmUGQaXA9sti3InmjE5HUzT\n/H3E8+ec7EgQBEFIDYLBsNPBrudgM3as7XSQgLZYkSKSgtvYdR3KylqPdLCLSIKkV8SDXUgSxOkg\nJB47vUI6VwheYxj0AhYCFwF70E6Hp4AydODBKeA2J9pSllcQBEFoxI4dPo4d05OV8eMbT5LPP19P\ndrZs8XH6dIeblpLYqRU5ORbDh8udLKH92A6EPXt8WK3MU+x2mbm5Fr16yYQmVnr2tMjK0uN16JA4\nHYTEceIEnDhhRzrId1TwnEeAXsC5wDAg0rP9JnClU+G4u1copXbScnpFEDgOrAUeN03zQ6eGCYIg\nCN6walXYH9000mHMGP06EDD46CMfF14ok+i2kCKSgtvY9RlqagwOHjTo0yf6ZZld86G42MInt5li\nxu/X+fV79xo60qGX1xYJ6Yq0yxSSjCnA/7MsNhtGsxqNe4D+ToWd/AS9hC4UWQh8CLwW+lsIZAPr\ngMuBFUqpTzo1TIgNy4L33vPx4ov6b2t3PARBEGJh5Ur9O1NUFGwUZgwwZkz4okhSLGLDjnQYNUpS\nKwR3GDgw/L1srZikXfNBikjGj51fL5EOQiKJbMsq6RVCEpCFTqGIRiFQ2x7heNkF7AY+Y5pmg1FK\nqS7AK8AW4JbQ89noUAwhASxenMXs2bns2mX7jvIZPDjIrFlnmDKl3lPbOora2lo2btzQ4vt+v4+C\ngnyqqqoJBKJfdJWWnkdOTk6iTPQEGZfoyLhEp+m4LF06Hshh2LDDrFmzCWg8Nv37j2Pv3k4sWXKM\n8eO3NGyXjmPTXg4eNCgv1+foSIeN0DJtfU9BvqtVVbnopmLwzju78fsPAs3HZfv2C4Es8vMPsmbN\nViA9xyUR2KHu4nQQEsn+/WGngxSSFJKA99G1G16J8t6XgHedCjtxOtwJ3BbpcAAwTfOkUmoe8KRp\nmnOVUk8Cf3BqmNA6ixdnMX16HsFg4zscu3b5mD49j2efrckIx8PGjRsoL59EaWnr6xUUtLQ9wBLG\njr3AbdM8RcYlOjIu0YkclxMnulFWdhSACy54kMLCRxqtW1AA5533B/buvYnt249RWDgppAHpODbt\nRYpIxs/GjRu4+olJ0LsdIgfh9W+n3/HYMDa9DPDVQDCHn/3reX525GfNV7aACl145bVDT/Da/P9J\n23FJBPZdZykkKSQS2ymdn2/RvbvHxggC3AcsMQzeAeajf0mmGgY/QKdeXOZU2InToSfQwiU53dCh\nFwBHHVkktIllwezZuc0cDjbBoMGcOblcc009RuuFrdOC0lIYP9759pWV7tmSTMi4REfGJTr2uLz+\n+gQsS18E3Xjj8qhjdfXVq3j11ZvYvXs455xTQLduVUD6jk17kCKSDukNFHttRJLSGyi2oPtuOHo2\nBEqij9XJ3hAI9bsduEvGM06Ki/X3tbIyB4JZQPrfyBE6Hju9oqjIyohrdiG5sSyWGwaTgJ8BD6EL\nSd4LLAeutCwc12t0UtNhCfAzpdQlkQuVUpcBDwJv2YvQqRiCy6xY4Y9IqYjOzp0+3n9f8q0FQYiP\n5ct1yHZOzhnGjl0TdZ3x41c2PF+9Wu6YtoZdRHLkyCAS0S64Sved+u+xwdHfPzYoYt3dCTcn3bAj\nHSzLgFP9PLZGSFfC7TLFKS0kB5bFcsviCnSQQX+gq2VxmWWxvD26TiIdbgEWAUuVUseAQ+i6vt2B\nNaH3QXey+Hl7jBOiE5n/5cZ6giAINrbTYdy4VeTmRq8XNGbMWvz+egKBLFatGsfkyUs60sSUwo50\nkNQKwXW679J/j5VEfz/SGdFNnA7x0ii//lR/dJt6QXCXiopwpIMgJBOWRTVQ7ZZe3E4H0zT3ARco\npa4BxgFFQAWw0jTNVyPWe8YtIzsEyyLrvWVwopKsroXUj78Y1+KcXNbu2zfyxGQxkaX0o5xy+rGU\nidgtVRuv55CEjguwFCgH+kGE6cmvn8hxSbS+jEsL2iT4eEz+c0wwaLBixUUAXHxxhEO7ydh0mlhN\naelG1q8fzcqV7chVcdH2DteOQf/AAaPhLtbo0XHexZLzYyv6MHE39DsB5V1h6SBSw3a37S60Ix0G\nQdAAw2qsf2ygft9XB13L22l7Kp/bnWk36txzakAr+ql6PGbeZ5oU+k20K8p1oz/Xikim6rin0Wfq\nuu0diGHwW6CzZXFjlPdeBKosi5udaDuJdADANM1XiF7ZMuXIWfwyXWbfh3+X/gHvCnQaXMLJWQ9Q\nO+W6pNO+6KIAgwcHGbPrJeYxg2HsaHhvO0OZwTzWlVzPhAntu7OWyHFhATADIkyHocA84Ib2SSda\nP6Hjkmh9GZfoJPh4TJVzzKZNI6mq6gZEOB1aGJubBz/Nd3iiXU6HVBkXp/qOi0jK+bFFpm6Gef+E\nYRH1Q7YXwoxPwcIR7dNOpO0JsduOdAjmMHVNd+Ytq2ysn/t7ZnApCwvGgN/59UAyfJe80O7Vy8Lv\ntwgEjFCkQ3NS9XjM1M/Ua/1o2itC1+1FRZ9pp+WpO+7p9pm6absHXAXc3cJ7fwN+4VTYSU2HtCJn\n8csUTL+p4WCx8e/aScH0m8hZ/HLSaRsG/GzCX5nPtEYOB4Bh7GA+0/j15L+0y8mWyHFhATANmpiu\nX08Lvd8eEqif0HFJtL6MS3QSfDym0jnGTq2AkNOhlbH51ltPMZUF7N49mEOHenpue0dpx6Nvp1bk\n5looFeNdLDk/tsjUzTD/L40neKBfz/+Lft8pibQ9YXaHajpMZQHz/1HZXP/MYeYzjanZf3S4g+T5\nLnmh7fdHRIxGcTqk6vGYyZ+pl/otadvX7RPKFzrWbk0/2cc9HT9Tt2z3iF7o0gnROAL0cSrsONIh\nLbAsusy+DyMY/WLQCAbpcu9Mqvr0iT9MxrLo8sMZCdGuq7W44m934Se6tp8gE/5vBv7P93IW3uOi\n7d22bqFzV2gw1QJuj3jdlGDo/SIawhM7b4LgiU1kRbGnvfqtaTcjgZ+p2/oyLtHp0HFx2fZEatvj\ncmBRHy7kfYr6ltOvrKLVsfFZFo9yO+UUse2Pw+je/XByHDNJdDzWvJ3HhWShBgXotKGm2bqJPh5T\n9TzQbesWLjwYsrdBHx59FfwtZA36Q++Xd9G2cwi6bUkC2+O1m9Ztb6RfvQ1YwaPc3rI+QR499jDl\ne/B0XDpc3yXtqwry2LTPD0eqYW+kfmocjx2qnWj9NLbdT5CL/3Q31Z/x/ro9bbQTrR+Dduc5P6L2\nmmtTLdViHzCBcGOISCagSyo4wrCszClccujQiUb/bPbyd+l+ffvDmQRBEARBEARBEATB5tii16i7\nSDd87NWra9J7HwyDB4DvAd+0LP4SsfwLwG+BRy2Le51oZ3Skg2+/Y2eNIAiCIAiCIAiCIEQlBeea\nc4AxwIuGwbPoyIYioBPwKjDbqXBGOx2CfYtiWu/EvIepP3dUXNpZG9bTdeadrmrX1MB3vpNPz33r\neJpvtbn+LTxFv8+Ucvvt0dvetYSbtm/duoWuXW9j5MjQgjUQg+nwFPqQBzZtghMnHuecc4a7rt+a\ndlMS8ZkmSl/GJTodOS6Q2LFxe1x27vwjDz/yMADP/e7rjKjZEtPY3MJT7OnRn3nzruXkSe+PmWQ5\nHt//xqPc/rsLAXj8sWqGDm0egpno4zFVzwNbt27h9rdu05mlIcZUwNOL25TnlmthbV/gEDw62Xvb\n47YbWrW9mf5Lt/H0ocdj1/doXDpa3y3tBQuyePo3uUAQvjkRfLogZ6ocjx2pnWh9sd0b/VTVTrR+\nrNqxzjWTBcuiFrjWMLgKmAycha7l8KZl8a/2aDtKr1BKZQPTgfHAAOA20zS3KaVuBNabptmO8jmJ\no2l6BZZFjwljmhUAiaS+ZAiVK9Y4yvVxW/tHP8rl6adzAIvKnsPofvjjFtct7zyM4lNbAYMFC05z\n6aVxVK520fY1a1ZTWDiJ8XaBews4m+ZFzCIZBmjTAVi5EiorlzB27AWu67em3YxEHi8u68u4RKdD\nx8Vl2xOpvWbNal58cRm/+9195Oef5vjxbmRn1bc5NlW9u9Lt4HHA4OWX+5OT80fvj5kkOR5/+PmN\nzPtFHrm5Fh9/fJLs7ObrJfp4TNXzwJo1q7l6/iQojtSHbY82L9oXybYecM53te3sg9enJYHt8dpN\n67Y303/5MbatfrhZUelG+t2yOOd79Z6OS4fru6T98stZTJ+er198byB03xPST43jsUO1E60vtnuj\nn6raidZ3oJ3s6RWGQR7wbeCflsVHbuvH3b1CKTUEMIG56MuTK9EdQgAuB2a6Zl2iMQxOznoAyxd9\nGCyfj1P3/8TZge6y9nvv+UMOB/jUpwIw7yetagd+OpsePbSP5c478zh92jvbG2uj27K1dOT50EeW\n069lIvUTOS6J1pdxaUGbBB+PqXOO2bBBd64YN24V2dn1MY3NsR92wx6cTZviaJ2ZQuPiVH/deh1I\nWFoajOpwiK6NnB9b1NdtCAMtbB4wYOZVJJ/tibQboHA3M5hHoIUPNYCPmVdZyTcuidZ3SbuoKCJC\nqSqig0XKHo/ymXqi34Z2gNS1PWm1E62faNs9wLKoAR5ARze4jpOWmY+iW2kMQTscIkfzbbTjIWWo\nnXIdVc8+T33JkEbL60uGUPXs8+3qseqW9smTcPvteQB0727x0EM11LWhnffl63jggTMA7NrlY+7c\nXE9sj8oNwHy0yyqSYaHl7e1Dn0D9hI5LovVlXKKT4OMxFc4xgYDBpk06FeCSS94Lv9HG2BR/p5zO\nnU8CsHlzHE4HF23vaO1Y9det0z+vo0fHEWUGcn5shYUjYNoX9R3kSLb10MsXjnCunUjbE2k3hTtZ\nyA1MYz7bujfOmN3GMKblPcXCc+M8BiNIhu+Sl9rFxREBslUDGr2Xqsdjpn+mXum3pL2NYTxz9Ysp\naXuyaydaP9G2e8RaYGSbazkg7vQKpdRJ4Mumab6slPIDdcA40zQ/VEpdDrxmmmanBNjabpqlV0Ri\nWeStXE7Xk8c40bWQmnEXueedaqf2jBm5/P73Osrh6aerueGG+pi0LQu+8pV83nwzC5/P4tVXTzN2\nbIyt/lyyvVl4byNtYCm6REk/4DKi3hWIK70iTv24w+UbtBN4vLigL+MSHc/GxQXbE6k9f77Jt789\nDoCFC6/n+usXNdGnxbG54op/8847VzBhwj+ZMycnuY4Zj47H/fsNRo3qAsAjj1TzH/9RH3XzRB+P\nqXoeiJpe0cT2ibuh6CSUd4VlA5vbHlc4e0fZHovdbdjeTH/fOHhmpX7+1SuY6HtH63/wAMvKfggD\n3oPpl8Wk3SpJfm5PlHYgAMXFXQgGDfjUXXDJL6PoJ+/x6Jl2ovXTwPb8Y8eY/J9FLGUic+ac4dZb\n61zVT7lxT4PPtC3tZE+vADAMxgMvAD8EXrEs4omVbxUnhSTraTlgrA9w0rk5HmIY1F9yGRR2pr7y\nFNTHOTlPkPaSJf4Gh8N119UxdWqTi9dWtA0D5s2rYeLEzpw8afC97+XxxhunycnpGNvb1iaxcTGJ\n1E/kuCRaX8alBW0SfDwm5zkGYNOmgobnF1+8PIo+LY7NuHGreOedK9i8eRyWtT6u/Wrt5B0Xp/p2\nlAPAqFEO9ynnx1b0YelgdyXD2ok9x7hud/eIfOLjJSwd+45+vuwzeofdd7mzn5Q+tzvX9vuhR48z\nHD6c1zi9opF+qh6PmfmZeq4f0q442ZmloUVFRfHX12tLP+XGPQ0+04TZ3rG8BeQAfwYwDE6jb1PY\nWJZFNyfCTpwObwN3KaVeBexRtZRSBnAztK+ypRDm+HFdjwGgZ88gP//5mbidcsXFFvfff4aZM/PY\nvNnPo4/mcPfd8XWzEAQhvdm8WTsdhg7dTu/eh+Ladvx4fZe1qqoH5eX5nH++6+alHOvW+QHIy7NQ\nKqUvPoRkp9MRyD4JdV3gWEl4+fFB+m+33d7YlUb06hVyOhwf0PbKghAj+/aFnzeqHSII3vIQjZ0M\nruHE6XAP8B6wCViENuw24Fx0XewLXbMuw7nvvjzKy/Uds1/84gw9ezo7Br761ToWLMhi+fIsHn44\nh2uvrWf4cDnBCYKg2bRJO62jRjm0ge10ANi2rWsra2YOttMhriKSguAEAyjcCQfPg2OD9bIzXaA6\nVAesuzgd2kvPnro+VouRDoLggL17w8/79UvIHE8Q4say+HGitON2OpimuUUpdQHwY+DLQAC4FngT\n+Ippmq014xJi5LXX/Pz5z/pqddq0Oq65JnpOcCz4fPDwwzV84hOdqakxuPPOPP7xj9P4/W5ZKwhC\nqnLokEFFhW4J58TpMGTIxxQWHqWysgemmX5Oh9raWjZu3NDi+36/j4KCfKqqqgkEglgWrF59MZBF\nv377WbNmG6Wl55ETV16bIMRB912NnQ7HBjV+T2gXvXol1ukQ7zkmGul4jkn3cbGdDoZh0aePOB3c\nIN2PmY7GMBgADADWWRan2qvnJNIB0zR3Al9r786F6Bw9CnfdpdMq+vYN8tOf1rRbc8gQi5kzzzBn\nTh6rV/t55pls94rWCIKQsqxeHa4/0KhzRYwYhq7r8MYbn2Lr1vRzOmzcuIHy8kmUlra+XkGoLMbB\ng/04elTHzY4Zcx/l5c8BDouPCkIs2HUdKkPpFccjnA6SXtFuGpwOJ4sg4Ae/824g0di4cQNXPzEJ\nejsUOAivfzv9zjHpPi6206FXL0si4lwi3Y+ZjsIwuBmYBRShMxrGAx8aBguAf1sWv3Ki68jpICSW\n//7vPA4d0hOBRx6poXt3d3RvvbWORYuyWbvWz4MP5nL11fWUlIh3VRAymZUrdchTfv5Jzj33I0ca\n48ev5I03PsX27V0JBNIviqq0lOgdIKKwaFH4YuULX1hFTQ1UVibIMEGAcDTDiWKozw5HPAB0K/PC\norSiIb3C8mvHQ7e9rW/ghN603K0lk0njcbGdDpJa4TJpfMx0BIbB94CfA79E12n8Z8Tb/wa+AB3k\ndFBK+YD/AqYB/YG8JqtYpmkOdWKMAC+9lMXChdrledNNtUye7J5HPStLp1lcdVUnqqsN7rorj7/9\nrdrVjjSCIKQWq1ZpD8HIkR+QleXsfGPXdaip8bNtmy+ja8asXq2dDvn5pxkxYjNr1nhskJD+2E4H\nyw9VA8LpFZ0PQE61Z2alCw1OB9ApFolwOggZh11IUopICknGd4GfWBYPGAZNbyGZgHIq7Gt7lWb8\nHHgKyAaWAC81eSxqeVOhNQ4eNLjnnlwABgwIMnv2mTa2iJ/S0iC33667VyxblsULL0hMlyBkKnV1\nsHat/k0ZNSr+1AqbceNWNTxfu9bJz0r6sGrVOABGj17n2IkjCHFRGNE289hg6VzhMg3pFSAdLATX\nkEgHIUkpRjeMiEYd0MWpsJP0iq8As0zT/InTnQrNsSy4++5cjh7VF+y/+lUNXRx/rK1z5521LF6c\nhWn6mTUrlyuvrHe3R7AgCCnBpk0+qqt1qNN558VfRNKmuHgfZ51VwZEjRaxZ4+dLX3Je+DaV0UUk\ndaRDpCNGEBJKZLHIypJweoV0rnCFHj1qwQiEIkmkg4XQfoLByEgHuf4Wkord6E6Ub0V5bwKw1amw\nk1tSebTsAREc8pe/ZPHaazrq4L/+q5bLLkvcHbLcXJ1mYRgWJ04YzJyZhyXnPEHIOOx6DgDnnrvC\nsY5hwMiROsXCjpzIRPbtK+bAgb4AXHDBao+tETKG/GOQe0w/PzY4nF4hnStcwe+3oFOFfiFOB8EF\nDh/WkYYg6RVC0vEMcJ9hMB0Ilcgm2zCYAswAnnYq7MTp8AJwndMdCs0pLze4915dGqOkJMi997qf\nVtGUceOC3HyzPuO9/noWL70kNUUFIdOw6zn073+a7t2PtkvLdjps3OijtrbdpqUkdpQDSKSD0MHY\nDobDI+CUdnxJeoWLdN6j/1ZJeoXQfioqwtMvSa8QkgnL4hfAb4HfAIdCi99Fl1B43rJ4wql2TDNN\npdTnIl4uB/5HKdUHeAM41nR90zT/7tSgTMOy4M4786iqMvD5LH7962o6d+6Yff/3f5/h1VezKCvz\n8cMf5jJxYoCzzpKTnyBkCrbTYcSI4+3WGjFCT7Jraw02b/YxenTm3b2JLCI5fPgWj60RMorCnXBg\nDOy+PLxM0ivco3MoAV8iHQQXKC8PV3CXSAch2bAsbjcMfgV8EjgLOAr8y7LY1h7dWG9vz4+ybBBw\nY5TlFjSrdim0wPPPZ7Nkif4YvvWtOi68sONOPp07wy9/WcO0aZ04fNjHfffl8uSTNR22f0EQvOPA\nAYOyMn23ZeTIqnbr2ZEOAGvW+DPS6WAXkRwzZq0UkRQ6FjvS4XSv5suE9iNOB8FFGjsd5GafkHxY\nFjuAHW5qxup0KHFzp4Jm926DWbN0twqlAtxzT+LTKppy+eUB/vM/a/njH3P429+y+dzn6rjqKrlY\nFoR0J7Kew4gR7Xc6dO9+hD59qjlwIJ916zKvg4UUkRQ8pfvO5sskvcI97PSKE/0g4Ae/XCcJzrGd\nDoWFFvn5HhsjCE0wDLKBr6MLRxYBFcAK4PeWRZ1T3ZicDqZpNvxyKaUGAhWmaTbbqVIqC+jn1JhM\nIhiEO+7I49QpA7/f4rHHasjL88aWWbPO8MYbWRw44GPGjDyWLj1F167e2CIIQsdgp1Z07WoxcOAp\nVzTPOecEBw7ks2ZN5gW77d3bn4MH+wBSRFLwgKZRDXmVkHfCE1PSEjvSwfLDyb7QbZ+39ggpi2WF\nW0t36xbEsnQxZkFIBgyDc4DXgIHAOuAAMBbthLjXMPi0ZWE60XZyO2pnaOfRGB16X2iDZ5/N5r33\ntM/njjtqPQ1F7tYN5s7VURbl5T7mzMn1zBZBEDoGO9Lh/PMD+F3yEZxzjp7kmKaP06fd0UwVpIik\n4CmFTS69JLXCXbrsCT+XFAvBIYsXZzFhQueGtOpdu/xMmNCZxYulmLuQNDwN1ALKsrjAsrjGsrgA\nGA7UAE86FXbidGjNH5cLdHyOQIqxY4fBAw/oif255wb4/ve9L/X+mc/UM3WqDl75/e9zePfdzLtT\nKQiZQm0trF+vT//jxrkXJmw7HQIBgw0bMuscYjsdOnU6JUUkhY6naSqFpFa4ix3pANLBQnDE4sVZ\nTJ+ex65djadeu3b5mD49TxwPQrIwAbg3VNOhActiO3A/cJFT4Vi7VwwHRkYs+oRSqqmrNw/4MvCx\nU2MygUAAvvvdfKqrDbKzdVpFTo7XVmn+53/O8PbbWVRWGnz/+3ksWXKKTp28tkoQBLfZsMHHmTPa\nfzx+vHtOh7PPDodzr1vnY8KEzMl7totIjh27Br8/84poCh6TdwLyjkDNWfq1r06X9ZawbXfoVAFG\nQKdXSKSDECeWBbNn5xIMRv9CBoMGc+bkcs019ZJqIXhNOfrXIxoWsN+pcKyRDjeiO1jMD+3wZxGv\n7ccfgUuBHzo1Jl2xLHjvPR8vvggzZuQ05FLPnFnLyJHJc3Haq5fFAw/o7hU7d/qYN0/SLAQhHYks\nInnBBe45Bjp3DjBsmNbLpLoOkUUkpZ6D4Ambp0JdRL/tzV+AR7fp5UL78QWgS4V+Lk4HIU5WrPA3\ni3Boys6dPt5/P3N+N4WkZTbwE8NgSOTC0OvZoYcjYo3leQR4Du0z/xj4HLCmyTq1wH7TNKX3SwSL\nF2cxe3ZuxMkmG4AhQwLcdpv3aRVNmTatngUL6nnzzSyefDKb666ro77ex4kT0LWrj/Hjg+KFFYQU\nx3Z8KhWgWzd3tceMCbJ9u5+1azPn4mnPngEcOtQbEKeD4AGbp8Jf5uu78JFUDtPLvzgNRiz0xrZ0\nomAvnOgPxyW9QoiP/ftju3COdT1BSCBfBLoDpmHwEXAQ6A2ciy4q+XnD4POhdS3L4vpYhWPtXnEc\nOA6glCoByqN1rxAaY+dvRQun2rXLx+uvZzFlSr0HlrWMYcC8eTVMnNiZkycNrruuE3V1tv35DB4c\nZNasM0lndzQsC5YunUh5eT/69Stn4sSl4jARBMJOBzdTK2zGjg0wf342O3b4OH4c150ayYgUkRQ8\nwwL+Oa+5w6HhfT+8MReGL5RUi/ZSsBf2IZEOQtz07Rvb/dhY1xOEBNIF2Bp6AOQAx4BlodeO+xvG\nXUjSNM3d4nBom1jzt6wkPL8UF1t87nP6Iw47HDSpUvBmwYKpnH32Nq644h2+/OUXueKKdzj77G0s\nWCChpkJms2+fQXm5+0UkbcaMCWuuX58Z0Q52PYfOnU+ilKNOUoLgjN0TdURDaxw9G8ou6xh70plu\noQ4W4nQQ4uSiiwIMHtx6OnVJSTCj6iAJyYllMSmeRzzaTrpXCDGQyvlblgXvvNOyUyGZHSagHQ7T\nps1nx47GF2I7dgxj2rT54ngQMho7ygFg3Dj3a8qUlgbx+/XJIVPqOtiRDlJEUuhwTvRzdz2hZQpC\nHSxO9IOgXD4LsWMYMGvWGXy+6BfOPp/F/fefkWhcIa2Rs2aCSOX8rVR3mMyYMY9gMLptwaCfmTPn\nJq3DRBASje106N7dYtgw9yfInTrB8OFad+3a9P+JkSKSgqd0LXd3PaFlbKeDlQUn+3pri5ByTJlS\nz9NP19C0MUBJSZBnn61JibRlQWgP6X9F6BGpnL+Vyg6TpUsnNotwaMr27WezbJmEmgqZie10uOCC\nAL4E/QKMHatDRNetSz7HpNuUlQ3k8OFegDgdBA8YtBQKt7e+To9tMHBZ6+sIbVOwJ/zHuyb8AAAg\nAElEQVRcUiwEBwwZEsQurnLPPbB4cTUrVpwSh4OQEYjTIUGkcv5WKjtMystjCyGNdT1BSCdqamD9\n+sTVc7AZPVqf+/bs8XH4cPI5J91EikgKnmIAn5oBRgvfZyMAV82UIpJuYEc6gHSwEBwRWefozjvh\n4oulI5yQOTiqBqiU8gMTgP5AXtP3TdP8QzvtSnns/K1vfjMPy2p+Rknm/C3bYdJaikWyOkz69Yst\nhDTW9QQhnVi3zt9QHDYRnSts7EgH0CkWn/xk8p0r3MCy4O9/vwGAvLzTnH321ja2EIQEMGKhbov5\nxlxdNNKmxzbtcJB2me7QtQIIAj6JdBAcYTv9i4qC9Onjo7LSY4MEoQOJO9JBKXU+sANYCrwIPNfk\n8Tu3jEt1pkypD4VSNSbZ87dSueDNxIlLGTq09VDTYcO2cdllEmoqZB6rVulTvs9ncf75iXMEjBgR\nJDc3vYtJ2h1yXnjhJgBqajoxfLgphWoFbxixEL57Dnz9cph2I3xjon4tDgf38NeHHA+I00FwhB3p\nMGqUFBwWMg8nkQ5PAseBrwGbgFpXLUojyssNduzQJ5ivf72OT386m65dqxk3rj4pJ+yRTJlSz7PP\n1jBnTi47d4Z9U1lZFr/5TXI7TObOncHnP/93osWT+nwB5s6dmfTjLwiJYOVKfT4aPjxIly6J2092\nNpx7bpDVq/1pWdfB7pDTtGCt3SFn/vxp3HCDTPaEDsYABi/12or0pmAvnCiGKkmvEOKjvh42bdLX\n0+edJ04HIXkxDD4FTCN6RoNlWVzpRNeJ06EU+IJpmm872WEm8Y9/hIf3jjvqGDMmm8rKIPXJOV9v\nxpQp9VxzTT0rV2bx2mv5PPYY1NcbFBQkXy2HSLp3P040h0NJyQ4eeuhumQwIGYllhYtIJrKeg83o\n0QFWr/azZo0PyyJtHH2xdsiZOnVh2vzPgiCEKNgL+yZIpIMQN9u3+6iu1j8Kdt0jQUg2DIMZwM+B\nXcBmdKCBKzgpJLkVKHDLgHRm0SLtdBg9OsCgQck9UW8Jw4BLLgkybx4UFur/4fnnsz22qnWeeupW\nALp3P8rjj3+rYfncuTPF4SBkLHv2GBw8qE/5iaznYDNmjN7HoUM+ysvTZ/YtHXIEIYOxO1iI00GI\nE7ueA4jTQUhqbgMesyyGWBZTLIsbmj6cCjtxOtwJ/EApNdzpTjOBigqDDz7QTofrrkuR0IZWyMuD\nL31J/x+vvJLFoUPJOYnYv78PCxbo78M3vvEct976ND16HAFgyZLJXpomCJ5ip1ZAxzgdxo4NX1Sl\nU10H6ZAjCBmM3cGiqhiC0gBOiJ0NG/TvYI8eQYqLU/NGpJAR9AAScofWyRnzMaAY+EgpVaaUWt/k\nsc5lG1OSxYvDqRXXXVfnoSXu8dWv6v+jrs7gxReTM9rh2WenU1+vbbvllqfx+SwmTVoCwFtvidNB\nyFzs1IqzzgpSUpL4C55hw4J07qz3s25d+lycS4ccQchgbKeDlQUn+3hri5BSbNgQrucgqXdCEvMy\nkJBQTSdXgquBfwDPA/8KvY58fOiadSmMnVpx3nmBDrnA7wiUsrj4Yh3t8Pzz2QSTLDosEPDxm9/c\nDMDkyf9Cqa2h528BsGXLCMrLizyzTxC8JFzPoWMuePx+GDVKR1SkU6TDkiWfaHMd6ZAjCGlKtz3h\n55JiIcRIMBiOdLB/FwUhSfkdcJNh8KBhMNkwOL/pw6lw3IUkTdP8utOdZQoHDhi8/74+uXz2s6mf\nWhHJTTfVsXx5Frt2+Vi2zM/llyfPyfO11z5NWdkgAG699amG5bbTAWDJkkl85Sv/1+G2CYKXnDoF\nH32kfcwdUUTSZsyYIMuXw7p1/rQoJvnTn/6AH/94TuiVhXTIEYQMw450gFAHi5WemSKkDrt2GZw4\noX8UpF2mkOT8M/T3ntAj8s65EXrt6E5S0sS8KqUmKqUWKaX2KaWCSqnPRllnjlKqXCl1Win1hlKq\n9WpeHvGPf2RhWfrkki6pFTbXXlvfUFDyD39IrhQLu4Bknz77uf76lxqWK2VSVKRDnSXFQmgJy4J3\n3pnIiy/eyDvvTMRKjwAlQE/6AwF9TupIp8PYsXpfx48b7NyZ2rPwuXNncO+9PwV0JMMzz/wXw4Zt\na7TOsGHbpF2mIKQzXcuB0KRRIh2EGLGjHEBHQAtCrCilblNK7VRKVSulViilxse43aVKqTqlVLwZ\nCJOaPCZHPOzXjogp0kEp9SjwC9M0y0LPW8MyTfMOB7Z0BtYCzwJ/j2LDPcB3gK+i23g8ALyulBph\nmmatg/0ljJdf1sNaWhpgyJA0mrmgC0p+8Yt1PP10Dq+8ksXBgwa9e3v/P+7ePZDFi6cAMH36s+Tk\nhJ09hqGjHV544T/F6SBEZcGCqcyYMa9RV4KhQ7czb96MtJhA2qkVfr/V0FWiIxg9OryvtWv9DBmS\nmpFfL7zwfX71q7kADBmygyVLJtG//z6mT/8tS5dOpKKiiH79yrnssmUS4SAI6Yy/Hrrsh5P9xOkg\nxIzduaJLF4vBg6NHyQlCU5RSNwIPATcDH6CbObyulDrHNM3DrWzXDfg98CYQV/EZy+Jt5xa3TqyR\nDtcBhRHP23rEjWmar5mmeb9pmi8R/dt4B/AT0zT/YZrmR2jnQz9gqpP9JYoDBwyWL0/P1Aqbm27S\nE/r6eoM//zk5oh2eeeb/YVk+DCPIzTf/ptn7dorFrl0l7Nw5uIOtE5KZBQumMm3a/GZtEHfsGMa0\nafNZsCCpTjGOsDtXlJYG6dy54/Y7eLDVEBmVqnUdFiwo5le/egiAwYN3NjgcQDs0L798KTfe+Bcm\nThSHgyBkBHaKxfEB3tohpAzr1+vfv/POC+BLmhhzIQW4E3jaNM0/mKa5BbgVOA18s43tngJeAFYk\n2L64iOnQN02zxDTNdRHPW3sMcdtIpVQJ0BdduNK2qQp4H7jY7f21h8WLw6kVn/1seqVW2JxzTjCp\nCkrW12fxv//7XwBcc80rDBpU1mydK69sOHQk2kFowLJgxox5BIPRJ8TBoJ+ZM+emdKqFZcGqVR1f\nzwH0pNyOdli7NvWutJ59NpunnjobgIEDd7NkySQGDtzTxlaCIKQ1DW0zJdJBaBvLCtdUknoOQqwo\npbKBC2g897XQ0Qstzn2VUt8ASoDZse7LMKgyDC4IPT8Ret3iw+n/lCpXgX3RhSsONFl+IPRe0mCn\nVowcGWDo0BSeqbSBHe1gF5T0krffvp4DB/RhEFlAMpJBg8oYMmQHIE4HIczSpRObRTg0Zfv2s1m2\nLCHdgzqEnTsNjhzRp/rx4zs+l9Su67Bhg59ACqWy/u532fzgB3kA9OlTxpIlkxg8eLfHVgmC4Dl2\nBwtxOggxUF4e/g2Weg5CHPREF2yMee6rlDob+CnwFdM04/FwPQRURDxv6+GIuLtXpDI+n4HP13L8\nq9/va/Q3Xg4epCG14vrrA2RlhXXaq90aidRuSX/q1CD33mtRWWnw/PM5TJ58ptVt3bAhcjwjl//9\n77qA5IABZXzmM6+2qDF58lt8/PFQ3nprcqNK+i1px2JT5N94qK2t5aOPNrS6js9n0KVLHidP1hAM\nRndgnXvueeTk5LRoW3vwYlwSrd90m/LyfjFtF7me03GJ3H9HngfWrAmf5i+6yGrxe+SWDU31zz9f\nH7unTxvs2OFn5Mjmx3KynR+fey6Le+7JBaBnzzM88cRkhgzZ2S4bEjXurR2PqXoeSPTvRqz7T0bb\nU/UzTfRvXlv6rv6e2pEOJ4oh6ANfbNf26faZJlrfy3GJ3H977di4MXxjbuxY/RuczOOeyO9SW7R3\nXNL5u9QWSikfOqVilmmaO0KLY0r6tKxwVIRl8WP3rdOkitNhP3rg+tDY49MHWBOrSI8enTFiSLot\nKMiP1z4A/vxnGlINvvrVHAoLm3/hnGrHQiK1o+l//evw8MM6paS2Nos+UUqVuGVTQUE+hYXNk9Er\nK7uzcuUoAG6++Tf4/S3/+E+e/Bb/+7//j/37i9i8eQQjR25uVTse2+Jl5cpN7NlzBaWlba/bpUv0\n5Rs3QkHBB4wf37yQrRvj7sW4JFq/6Tb9+pXHtF3keu0dl2h2uElT7XXr9N8+fWD06E5R6w4k8ns6\naVL4+datnbj00ta3TxSxav/2t/D97+vnRUXw61+bDBiwo/WNYth3tGMm0d/TVD0PJPp3I5F2JNr2\nVP1MV67cxCd/fQX0drxbOAgf3Bv9N6/d+q1oN/t/badDMBtO9Yau+2PaRbp9ponWT4ZxccOOrVv1\n3/x8uPDCTmRFzLyScdwT+V2KFafjkgzHjIuf6WEgQPNCkH3Q8+KmdAXGAWOUUo+HlvkAQylVC3zK\nNM1/R9uRYXA3sBRYbVkkrCBhSjgdTNPcqZTaD1wJrAdQShUAE4DHW9s2kqNHT7UZ6VBQkE9VVTWB\nQPx5V3/6Ux7gZ8SIIH36VFNZ6Z52ayRSuzX9L37R4OGHO1FfD08+WcsddzSvYVFVVU1BQfttqKqq\nprLyVLPlf/5zDwCysuqYPv3ZVjUmTVrS8PyttyY3OB1a0m6L9ox7VVU1paXQjnNyg040290Ydy/G\nJdH6Tcdl4sSlDB26vdUUi2HDtnHZZcsaaTgZF/DmPLBsmT4vjR9fz7Fj0SOSEvk97dQJ+vbNZ/9+\nH8uW1TF1avNmQ8lyfvzTn7L4zndyAIPevYMsXFjDiRPH2m2DV9/TVD0PVFVVx72/lnTSzXY39D0b\nl95Acdy7babT4ri0Uz/mMS+IqOtS1T9mp0O6faaJ1vdyXMC9sXn//Vwgi9LSACdO1Liq3RJef1e9\nOh6T/bsUjzPDNM06pdRq9Nx3EYBSygi9jtZJsgo4t8my29BtLj+P7vzYEj8P/a0xDFYBy0KP9yyL\n4zEb3QZJ43RQSnUGhhEOBRmilBoNHDVNcw/wCHCfUmo7euB+AuwFXop1H8Gg1WIoUCSBQJD6+vgO\n9kOHDJYt0yE1111X1+L2TrRjJZHa0fSHDoWLL65n+fIsfv/7LL71rTPNqvK6dTKN9r9VV8Prr2sH\n4NSpCykqav2Hv2/fA4wcuZFNm0p5663JfOc7j7eo3V7bYtnGDVratxv6XoxLovWbjothwLx5M5g2\nbX7UYpI+X4C5c2c2ig5w4//qqPPAyZOwaZP+Up5/fn2r5yW39x3J6NFB9u/3sWaNr9X/28vz41//\nqh0OlmXQs2eQv/2tmpKSIGvWJO67lOjvaaqeBxJ9PCZyezm3t7yNG3gxLs207UgH0B0sile5q++A\nTPi97qj9uq2xbp3+DT733EAzHRl3d7dPZdtb4JfAcyHng90ysxPwHIBS6kGgn2maXwsVmdwUubFS\n6iBQY5rm5jb20xO4BLg09LgT+AEQNAw2oR0Q7wLLLAvHxa1cSzxRSsWfvNOYcehUidXoopEPAR8S\nqr5pmuZc4NfA0+iuFfnAZ0zTbH7bzANefTWLYFDPTK67Lj1bZUYjsqDk0qUdW1Dy5ZezOHFCt+xs\nqYBkU+zWmf/+9ycIBFKljqqQSG64YSFPP31zs+V5edXMnz+NG25Y6IFV7vDhh/6G89K4cd5VzR4z\nRhfP2rjRR21SnLEb8/e/Z/Hd7+ZhWQZnnaUdDkpJlXFBEKLQtRwInR+kmKTQCgcPGuzfL50rBGeY\npvkX4G5gDnqOPAq42jTNQ6FV+gLt7t1rWVRaFostix9aFlcABegOGTOBrcBU4A/Ax4ZB8xaBMRJ3\npINS6iagu2mavw69PhdYAJQopZYBXzRN82C8uqZpvk0bThDTNH8MiStw0R4WLdJDqVQgoy5Wr722\nPqKgZDZXXNFxlXmfe077uQYM2NoodaI1Jk9+i8ce+y6VlT1Yt240cZQEEdKYgoITDc8vvXQp7747\nkbq6LK666g0PrWo/q1ZpR2BWltXQutIL7A4WtbUGmzb5GDMmec6RL72Uxbe/nUcwaNCjR5D586sZ\nMSJ57BMEIcnIqoMuB+BkkTgdhFaxW2UCjBolnSuE+DFN8wngiRbe+0Yb284mjtaZNqG6Du8D7xsG\nLwKXATcB19COxBsnt3pn0ODiBXT0QS3wPaAI3aojozhyxODdd/XFfSZFOQDk5cEXv6ijHV55JYuD\nB2MqlNpuPvrI1zCh+tznnsLni6096RVXvI1h6MNXWmcKNnZLzB49jvDggz8EIBDI5r33LvHSrHZj\nf0dGjQqSn9h6Va0yenT4J2PtWm9b7Eby8stZ3HqrdjgUFlr89a/VlJaKw0EQhDawUyyq2n2TUUhj\n1q/Xv3fZ2VZG3ZAUUhPDwDAMRhsG3zYM/mgY7AT2oNM8atA+gFbKgbeOE6fDYEI5I0qpnsBE4C7T\nNB8D7geudmpMqvLKK1kEAnqy/dnPZpbTAeCrX9VOh/p6gxdfzO6Qff7hD3o/2dlBpkz5fczb9ehR\nydixOrpBnA6Czbvv6nPopZe+y4UXfkB+/mkA3n77Ci/NahfBYNjpMG6ct3dYzjrLYuBAfcG1dm1y\npDW98koWt9ySRyBg0K2bxV//eprzzpOLQkEQYqDB6SCRDkLLrF+vf++GDw+Sm+uxMYLQAobBLMPg\ndeAYsBL4BnAEXdehxLLob1l8wbL4pWWxwul+nFz9BQG7fsMkoA6wY9sr/j97dx4fVXn2f/wzSzYC\nYZV9Jzggu4isAXGtggpKodbHrbRqtXWphbZa6+NS20rr1rq19Ve3RxFQQU1VVBCysYisEYeAbLLK\nmgSyz/n9ceckLEmYJLMm3/frlReTyZk7F5OZM+dc576uG2hd12Ci1QcfmNKK3r0bV2mFrXdvHyNH\nmmTLG2/EVCwbGiz5+TB3rkk6jB27nxYtDtXq8XZfh6VLx1JaGjG9VCVM8vKasmbNYMAkHeLiihk5\nMgswvT+i1ZYtTo4csfs5hH9ap93XYfXq8M90+OQTFz/7WTylpQ6SkkzCQfW2IuI3ewWLo5rpINWz\nZzqotEIi3EOYRpKvAedYFsMsi7sti9mWVfceDqeqS9JhLXCHx+PpB9wFLPJ6vfY6bF2BWvdziGaH\nDlHRQPHKK0tP6nLfmNizHULRUPKdd2I4dsw80RMm7K714+2kw7FjTfn663quWSlRb/ny4RUrV9hL\nY44btwSAlSuHcfx4GOsS6uHLLyt378OGhf+Ax046eL1OjtVtBbOA+PRTFz/5SQIlJQ6aNbOYM+d4\nRPWYEJEoYM90yOsEvkZ64Cc1OnIEduwwn8OaRScR7m7gQ+BqwOtwsM3h4E2Hg184HJzrcARm4Ym6\nDHI/MBZYBwzAZEdskzFLejQaH30U06hLK2wTJpTSsqXpq/D668ErsbAseOUVM/4555Rxzjm5tR5j\nzJh03G6TJFm5UiUWjZ3dzyE2toihQ1cBcMEFXwBQUhJLVtbIcIVWLytXmkRKhw4+OnXyr+dJMA0Z\nYg66fD4HGzaEZraDZUFmppPZs82/n3/u4pZbTMIhMdFi9uzjnHuuDgZFpJbspIMvBo61DW8sEpHW\nr6/8nNNMB4lklsXfLYvrLIuumDYKvwUOYMoslgNHHQ4WORw85nBwRV1/T62TDl6vNwMzo+F8oLvX\n6z1xgeKXgd/XNZhoZK9akZxc1qg7noeqoeRXXznJzjY78ptuKqnTzJJmzfI5/3yTG/vySyUdGju7\nn8OwYSuJjzeTts4/fwVxcYVA9JZYREo/B9vAgWU4HCb5EYq+DqmpboYPT2TixASuu47yfxMoLnbQ\npInFW28VMGxY491ni0g9NN9ZeVvNJKUKdj8Hp9PinHP0WSPRwbLYWV5WcZdlMRRoAUwBjmGSEe/X\ndew6Hfl5vd48r9e7yuv1Hjnl/v96vd5NdQ0m2hw+rNKKE4WioeSrr5p2Ik2aWEyZUlLncewSi/Xr\nR1FUFBmN7ST0SktdFTMZRo/OqLg/Pr6ooq9DNDaTPHrUlDFAZJRWADRrBsnJ5sAr2H0dUlPdTJ8e\nz7Ztp763HYDFXXcVM2JEZDwvIhKF7JkOoGaSUiV7pkPv3j6aNAlzMCK14HDQ3OHgBw4HjwIfAPOA\nCeU/zq7ruHXqoufxeDzAtUBnIP6UH1ter3d6XQOKJh9/7Ka01GQaGttSmVWxG0pmZbl5440YfvGL\n4oCOf+QIzJ9vXrLXXltCs2Z1H+vCCxfx2GMPUlwcz8aNSYwYEaAgJaqsWzeQY8eaApX9HGzjxi3h\niy/Gs3z5cAoK4klIKAxHiHWyapULy4qcJpK2wYN95OS4grpspmXBww/H4au2ztrB22/HcO+9xY0+\nUSwiddRsV+VtJR2kCuvXq5+DRAeHg16YRpKjy7/6YiYmFGBWs3gGSAeyLIujdf09tb7E6/F4bsBk\nOe4HxgFDqvhqFN5/31zN79nTp7XdywWzoeTbb8dQWGjOEm6+ue6zHABGjsyqmD6/Zk3Lescm0cnu\n5wAwalTmST+z+zoUF8exbFl0ZaXs0orYWCuiDnjsZpLffuvkaJ0/tmq2bJmrihkOJ9u61cny5eFf\nRUNEopS7BBL3mttawUJOkZ8PmzebzyH1c5AokAO8iunNmAP8BhgJNLcsLrAsfm9ZfFyfhAPUbabD\ng5hpFj/xer3H6/PLo9mRI7B0qTloveqquvUWaIgmTCilVSsfhw45ef31GO68MzDjWha8+qpJ8gwd\nWlbvE6n4+CJGj85g0aKLWLOmRSBClChk93Po2/drWrc+eenV4cOXExtbRHFxHF98cQHjx38Rhgjr\nxk46DBoUWWuD20kHgLVrXYwdG/iDsb17/dsZ+7udiEiVkr6DY+0100FOk51dOdtQyzFLFJgOZFgW\nQW2RUJdi9o7AvxpzwgFMaUVJiUorTmUaSprn47//dXP4cGB6O6xb14LNm+0GkoEp27joos8B8HqT\nyM8PyJASRSyrcqbDif0cbAkJhQwfvhyIrr4OPp8pr4DIKq0A6N/fh9ttN5MMzkyD9u39W6nD3+1E\nRKpkN5NU0kFOYZdWAPTvH1mfwyKnsiz+E+yEA9Qt6bAU6B/oQKLNBx+Yk+nu3X30768s5oluuKGy\noeTChe0DMmZqakcAmje3ArY0qd1M0udzsGyZplo3Ntu3d2P37k7A6f0cbHaJxbJlIygsjKApAzX4\n5hsHeXmR188BICEB+vQx+8tgrWDRo0dlYqOmbYYPj6znRkSijN1MUqtXyCnWrTPHlD16+EhKCnMw\nIhGiLuUV9wNveDyeQuBT4MipG3i93kOnPaoBOXoUvvgidKUVxcXFZGevr/bnLpeTpKQEcnMLKCur\nPgHSr98AYmNjgxHiSU5sKPnRRx259VbTMb6uDh5sS0ZGGwCmTSsJWBfg8877ksTEXI4dSyItzc3F\nF+skxB/R9nqsjl1aAVXPdADTTPLRR6GoKJ7ly4fTpMnSUIVXZytXVibQImXlihMNHlzGhg2BayZ5\n4usxN9fNzJmDKxr8VsXptLjhhq9Zs+bASfeH+/UoIlGmIunQCXwOcDa+2VOBOB5oiPvetWvNZ1CX\nLgdYvfrr037eWJ+XaBaI1/qll14QpOiiQ12SDl+V//sC1Z9JNujLxieWVgTqqntNsrPXs3v3ePr1\nq3m7mrKp2dkAixkyZGggQ6vWjTeWkJXlZs+eBL788kKGD/+8zmN98MFPKC01V0Vvuql+DSRP5HaX\nMXjwUjIyJpKe3qBfsgEVja/HqtilFW3b7qNXry1VbjNyZBYxMcWUlMSyZMk4Lr88GpIO5r3SpYsv\nIksIBg/28cYb8N13Tr7/3sFZZ9UvRvv12KNHIg8//Clbt5rVSC666G02bTqXnTt7V2zbpUsOv/jF\nTMaPn3/KGBDu16OIRJmk8vIKXywcPwua7g9vPGGQnb2ey54fD23rOMB++OSOhrXvLSwEr9ccUy4t\neJKl8/5S+0Ea4PMS7QLxWrcujbxjslCqS9LhJ9TnsnUDYJdWdO3qC1ln+H79YNiw+o1x+HBgYvHH\niQ0l3333Nu68s25Jh7IyJ++9dysAo0eX0rt3YJ/v885bREbGRDZscHLoELRqFdDhG6xoez1WxZ7p\nMGZMerWzlZo0KeD881eQkTGGL764gMsvfzSEEdaNPdMh0korbEOGVMa1Zo2TSy6pf5y9e8fy8MPv\nsmHDSAB++ctneeaZuwFIS0thz54OdOy4u8a/dbhfjyISZeyZDmBWsGiESQfAnIR1CncQkeObb5yV\nSzZ7vtJz05DotV4vtU46eL3eV4IQR9TIzQ1taUW0shtKvvhiLEuWTGLfvra0a1f7D+SFCy9lz54e\nQGBnOdiGDTN9HSzLQUaGW01BG4kjR5qzYYNpTVNdaYXtggu+ICNjDFlZIykujuypjocOQU6OmekQ\nqUmHPn18xMVZFBU5WLPGVe+kQ1mZgwcffJPFiy8F4IYbXuPpp++p2DePHZtW35BFRE53YtIhtzN0\nWhW+WCRi2P0cAOiwOnyBiESY4HTyasA++cRNcXHoSiuimd1QsqwshldeublOY7zwws8BaNGimCuu\nCPzznZy8jmbNTJwqsWg8srJGYllm91ddE0nbuHFLACgsTCA7+/ygx1Yfy5ZV3o7Efg4AMTFUNN+t\nb18Hnw+efvpsFi++FoCrrlrAyy9Px9kIa6tFJMSSdlXe1goWUm7duvJTq8QdkHig5o1FGpFaz3Tw\neDxbOUN5hdfr7VnniCLcBx+Yp6xrVx+DBmnVipr07u1j4MAjrFvXgn/+81ZmzJhVq5OBHTu6kJo6\nAYDLLttDbGzgax+cTotBg46Qnn6Wkg6NiN3PISHhOEOG1HwlYtSoTNzuEkpLY/jqq3F07x6CAOso\nM9P8m5Bg0a9f5O6fBg8uY9UqF6tXO7HqmB+wLHjooTgWLmwGwPjxi3j77WnExCgZLCIh4C6GxH1w\nrJ1WsJAK69eXH0u2+armDUUambrMdFhQxddSwFE+3vzqHxrd8vJg8WKTdJg4sVSlFX64/PLdAHz7\nbS8WLbqwVo/9979/is/nwuHwccUVe4IRHgCDB5ti7pwcF3v36o/aGNj9HIYPXynp2VsAACAASURB\nVH7Gk9TExOMMG7YSgNWrxwU9tvrIyjL/DhpURkxMeGOpyeDBZhbGgQNOdu2q23vuySdjeeklU+5y\nzjkrWLDgauLjiwIWo4jIGVWsYKGZDgIlJfD11+WnVko6iJykLj0d7qnqfo/HE4tJOGytb1CRauFC\nN0VFdmlF4PsLNERjxhzgxRcPcPRoG1566TYuvti/hpIlJW7+/e+fAjBy5Me0bx+gdTKrMGhQ5aqv\n6ekupkzRldKGrKQkhuXLhwNn7udgGzduCVlZo1i7djQlJSuDGV6dlZbCihXmdqSWVtgGD66chbFm\njYvu3Ws3K+Pf/47hL3+JA6Br12M8/fTlNGuWH9AYRUTOKGkn7BmqpIMAsGmTs+I8gdZKOoicKGA9\nHbxebzHwD2BGoMaMNO+/b3I0nTv7GDIkcqcuR5LYWB8TJrwKwPz5pqGkP95//yr27OkIwDXXvBi0\n+AC6dDlOu3bm76kSi4bP6x1CYWECcOZ+DrYLLvgCgKKiJmza1CxYodWZZcHs2W7yy8+7hw6N7P1T\ncrKPxERTV7FmTe0+hubMcXP//fGAKXP705/W0qLFoYDHKCJyRvZMh6MqrxBYv/6EzzPNdBA5SaAb\nSbYBIu+IPADy82HRIpVW1MWkSf8CoLQ0hv/85xa/HvPii7cD0KXLDkaPTg1abAAOB4wZY64Mp6fX\nZRVZiSZr15p+Dg6Hj5Ejs/x6zKhRmbhcZgbMunUtghZbXaSmuhk+PJG77oqruO/BB+NITY3c17LL\nZUpAAFav9j/R99FHbu6+2yQc2rb1MXfucdq0KQ5KjCIiZ2QnHfI6gU8Hho2d3c+hRYtiaBK8smCR\naFTrpIPH47mmiq8feTyeh4GngEWBDzP8VFpRd927exk37gsA/vWvn1WuX1yNnJxkPvvsEgB+9rN/\n4XIF/6ptSoo5odyxw8n27TpwaMjWrjX9HAYMWE/z5rl+PaZZs3yGDjXLoa1fHzlJh9RUN9Onx7Nt\n28m78p07nUyfHh/RiQe7xGLtWpdfzSTT013cems8ZWUOWrSwmDOngB49tEqFiIRR853m37I4ON4m\nvLFI2NkrVyQn55lOdyJSoS4zHeZV8fUm8FtgIXBbwKKLIPaqFZ06+SJ+6nIkuvXWfwKmoeTnn19U\n47b//OetALhcpUyf/nLQY4PKmQ6g2Q4NmWVVznTwt5+DzS6xyM5uTkkE5B0tCx5+OK7aJJ7P5+CR\nR+LqvDpEsNnNJHNzHXz7bc1HZ1995eSGGxIoKnLQpInFm28e55xztB8WkTCzZzqAVrBo5Hy+ypkO\nycnqMSRyqrokHXpU8dUBiPd6vdd5vd4Gtyhtfj58/rlKK+rjmmvepXVr89KwkwpVKSyMqyjBuPrq\nBXTsGJrpaV27WnTtak5i0tLU16Gh2r07gcOHTV8Rf/s52MaNWwJAYaGLtWsDXZlWe8uWuU6b4XCq\nrVudLF8ema9nO+kAsHp19f+Pb75xct11TTh2zEFsrMWrrxZw3nlKOIhIBDgx6bD+OtiWcoZF5aWh\n+vZbB8ePmxOE5OS8MEcjEnlqfeTs9Xq3V/G1z+v1WgAej6fB9XT47DM3hYVmR3LllRFwiTMKxccX\ncdNNZ24oOW/eFA4eNFMUb789uA0kT2WXWKSn+zfdW6JPdnbzitu1nekwZkw6Tqc5Uc7MDP9sGH+X\nd43UZWC7dbNo2dK80b76qurEyPbtDqZOTeDwYQdOp8WLLxYyblxkr8whIo3IrqGVt7N+Da8shWdz\nYOOk8MUkYbFuXeXnWO/emukgcqqAXa7zeDxtPR7P48COQI0ZKexVKzp08OkKWz3YJRY1NZS0G0gm\nJ+dw0UX+La8ZKHaJxf79TnJywn8lWwLPTjp07ryTrl1rt6tKSsrD4zHdqDMzwz97oH17/zJj/m4X\nag5HZTPJqlaw2LfPwZQpTdi71/zs6acLmThRy9mKSITYOAnefev0+w8nw5x5Sjw0MnbSoXlzi3bt\nCsMcjUjk8fvMyuPxjPB4PC94PJ5Uj8fzd4/H07v8/nYej+c5YBtmucwPgxNqeBw7VllaceWVpTh1\nLlpnHs+mGhtKrl/fn4wMU29/220v4XSG9mTpxL4OKrFomLKzkwAzy6EuZVJDh34BwPLlLkrDfP47\nYkQZ3bvXnATt0cPH8OGROzNgyBAT27p1zpOez8OHYerUBLZvNzvcRx8t5Ec/UsJBRCKEBSycBVY1\nxwqWCz59QqUWjYi9XObAgWUqwxapgl+n0B6P53IgHbgVGIppFplVfv+G8u/fAfp5vd4bghRrWHz+\nuZuCAru0Qge99VVTQ8mXXjI9SGNji7j55ldCHRrt2ll4PPbSmUo6NDQHDzrYuTMRqH0/B9uQIaav\nw7Fjjoou1eHicMBDDxXhcFR9VOt0WvzhD0URffBjr2Bx/LiDjRvNffn58OMfN2HjRvMevO++Im67\nTWVtIhJBtqeYGQ01OdQbdowJTTwSVpZV2USyf3/NiBapir9HzfcDq4EuXq+3PdAK+AxYABwHhnu9\n3hu8Xu+m4IQZPnZpRfv2PoYNi9wrhtGiuoaS+fmJvPbajQD88IdzadPmYFjis2c7ZGS48elzo0FZ\nubJyd1fbfg62wYPTK07yI6HE4qKLSklIOP3+Hj18vPxyIRMmRHai1J7pAPCPf8AXXzi58cYEVq0y\nz+1Pf1rMzJnF4QpPRKRqeR0Du51EtZ07HRw5YjL8AwfqXEGkKv4mHfoCf/R6vbsBvF5vPjATcAO/\n9Xq9q4IUX1gdP26aSIJZtUKlFfV3akPJvXvbAfDWW9eRl2emvv/85y+ELT476XDkiIPsbP3BG5Ll\ny817uUmTPAYMWF+nMZo1O0qvXqZBVCQ0k1y40F3RLfuxx4qYPRtSUwtYtuxYxCccAFatcuFymSTO\nP/8J11yTULFk7dSpJTz2WGTP1BCRRqrZ7sBuJ1HtxCaSAwfqipVIVfw9am4FnLrn3FX+b07gwoks\nn39eeUB/1VWRfwAfLW699Z88+eR9lJbG8MorN/Ob3/yFF174OQD9+69n1KjMsMU2alQpDoeFZTlI\nS3MxYIA+PBqKFSvMQcGAAVm43XW/EjFw4BE2b27G8uUuysrAFcYJD3PmxADQqZOP228vpXXrOA4f\n9oW934Q/UlPdTJ8ef1pvF8PissuU6JXgKC4uJju7+sSjy+UkKSmB3NwCysqq/gzo128AsbGxwQpR\nIl23NGi5ueYSi1Y50LVupXyBEojXOjS81/uZnheo3X7A7ufQpIlFz54+1q0LeMgiUa82l+qqa4fT\nYOcRffCBeXratfNx/vkN9r8ZcnZDySVLLuDZZ39Jaamb1avPBcwymeG8stmyJQwY4GPdOhfp6W7u\nuEO15A1BYSGsXWs3eapbaYVt4MAjvPtuF/LyHGzY4GTQoPAkpvbvd/D55ybjMWVKSVSdoFsWPPxw\nXDUJBwAHjz0Wx8SJpZrpIAGXnb2ey54fD1Wv3Hxm++GTOxYzZMjQM28rDZMDuHSGWaWiqmaSjjK4\nZKbZLozq/VqHBvl6D/TzYs906N+/LKwXIkQiWW2SDos9Hk9VR9dpp9xveb3e5vWMK+wKCszUZYAJ\nE3TFLdDOPXcVS5ZcwJ49nXjwwccAcDh8NG9+JMyRmRKLdetcZGW5KCmBmJhwRyT1tWaNi+Jic/Q3\naFD9rjz173+0YjZMRoYrbEmH995zU1Zm/k9Tp0bB1IYTLFvmYtu2mneqW7c6Wb7cxYgRSvhKELQF\nOoU7CIlqfefD1ClmlYpDvSvvT9oOl99jfh4J9FqvWoCeF8s68aKGZseKVMffpMPDQY0iAqm0Inje\ne28Szzxzz2n3W5aTm256jcTE40yeHL4P65SUUp5/PpZjxxysXu3k/PP1IRLt7NIKp9Oif//l9Rqr\nWbNS+vXzsWGDi6ys8M2Gefttkw0799wyevf2UYsVkMNu717/Lv/5u52ISFj0nQ995sOmCfDW+4AT\nhj0XOQkHCbp9+xwcOFC5XKaIVM2vpIPX6210SYcPPzRPzVlnRfY699HGsmDGjFn4fFXPP/P5XMyc\n+QSTJs0P27Tq4cPLcLstSksdpKe7Of98dc+PdnbSoVevfJo0OVbv8UaNKitPOoSnr0N2tpMNG8wv\n/eEPo68EqH17/xav93c7EZGwcQCeVOi0EnYNhy0/gJRZ4Y5KQsTu5wCoD5hIDaLn0lgIFRTAJ59U\nrlqh+qzASUtLYcuWmte23ry5N+np4VvbumlTGDLEfHCkp+uPH+18vsqkQ79+RwMy5siRJhGZm+vg\n669DvxudO9fMcoiJsZg8OfqSDiNGlNG9e80HZz16KOErIlEk+WPz744xUJQY3lgkZOx+DnFxFmef\nraSDSHWUdKjCokUujh0zl9mvvFKlFYG0e7d/a1b7u12wpKSYv/vKlS4KCsIaitRTTo6zYv3swCUd\nKvcLGRmhTUyVlsK8eSYpesklpbRqFdJfHxAOBzz0UBFOZ9UzGZxOiz/8QctlikgU6fWJ+dcXC9vG\nhzcWCZl168ypVN++PvUAE6mBkg5VWLDAHNC3aeOruKIpgdGxo39rVvu7XbCMGWP+7kVFDr78UrMd\n/GVZsHRpCrNnT2Pp0hSsCJgdb89ygMAlHVq1gr59zWskMzO0r4+lS13s32923dOmRW9SdMKEUl5+\nuZAePU6+MtSjh4+XXy5kwoTo/b+JSCPUaQXEHza3N18W3lgkZNavt5fj1vmCSE2UdDhFYSF8/LHZ\ngUyYoNKKQEtJSaNXr801bpOcnMOYMeFd2/q888qIizNnzCqx8M97702id+8cxo1bynXXzWbcuKX0\n7p3De+9NCmtcy5ebv1/Xrj5atw5cf47Ro80BxrJlbnwhnFFpN5Bs1crHRRdF94n5hAmlLFt2jA8/\nLGD2bEhNLWDZsmNKOIhI9HGVQc/PzO3NPwhvLBISR4/G8N13WrlCxB9KOpxi4ULIz9eqFcHicMCs\nWTNwOqvOCDudZTzxxMywT6uOj4fzzzcxpqXVZmXZxum99yYxZcq80/p1bNmSzJQp88KaeLBnOth/\nz0CxZ0EdORK6vg65ufDRR+b1OHlyKbGxIfm1QeVwwKhRPqZNg5EjfWF/74uI1Jnd1+FwMhzsFd5Y\nJOg2b25acVsrV4jUTEmHU8yda/5t3VqlFcEyefJ85s2bQnJyzkn3JyfnMG/elLAul3kiu8Ri9Won\n+flhDiaC+bsiSThKLfbtc7Btm9nNBbop4Yn7h6ys0MyG+eCDGAoLzVn5tGnR10BSRKRBs/s6AGxR\niUVDZycdXC6Lvn0100GkJko6nKCoCN5/39y+4opS3LrAHTSTJ89n06azWbJkbEX9/6ZNZ0dMwgFg\nzBgz06WszMGyZSqxqE4kr0hyYj+HQM90aNPGok8fM2aomkm+/bbZKZ19dhmDBukAR0QkojTfBWdl\nm9vq69DgbdnSDACPx0d8fJiDEYlwOq0uZ1nwwgtucnPN91q1IvgcDhg7Ni3cYVRr8GAfiYkWx445\nSEtzc/HFmvlSlUhekcROOjRvbuHx+Fi7NrDjjxxZxjffuFi2zIXPB84gpnG3bXOwbJnZZU+dWqoy\nBBGRSJT8MXzfD7ZeCKUx4NastIbKnumgfg4iZ6aZDkBqqpvhwxN55JG4ivtmzownNVU5mcYsJqZy\nCr2aSVYvklcksZMOw4aVBSUhYDeTPHTIyTffBHd3OneuaSDpcFhMmaKDWBGRiGSXWJQ0hZ2jwxuL\nBE9xM3btagJo5QoRfzT6pENqqpvp0+Mr6r5t27Y5mT5diYfGzi6x2LDByaFDYQ4mQkXqiiTHjlWu\nnx3ofg62ESNC09fBsmDOHJN0GDu2jI4dI2AtUhEROV23peA+bm5rFYuG6+DgipsDBmimg8iZNOqk\ng2XBww/H4fNVPU/Z53PwyCNxYWmAJ5EhJcWcVFqWg8xMJaCqYq9I4nBU/aEbrhVJVq92UVZmfmmg\n+znY2ra1OPtsM3ZmZvCSDsuXu9i+3eyup07VLAcRkYgVUwTdl5jb6uvQcB04FzCzD/v310wHkTNp\n1EmHZctcp81wONXWrU6WL9fU+saqXz8fLVuarJNKLKo3fvxi4uMLqvxZ374bw9Ig1H7fxsRYDB4c\nvAMCuwQnK8sVtATl3Lkm4ZWYaHHFFeo3IyIS0eylM/cNhrz24Y1FgqM86dCrl4+mTc+wrYg07qTD\n3r3+XXr1dztpeJxOGD3anOQp6VC95567k4KCxPLbP2f27GncdtsLAGRn92fFimEhj8nu5zBwoI+E\nhOD9nlGjTNLhwAEnmzYFfpdaUAALFpjSiiuvLCUxMeC/QkREAumkpTMvDV8cEjwHTdJBTSRF/NOo\nkw7t2/t3WdLf7aRhGjPGnFRu2uRi3z4loE6Vn5/IU0/dC8BFF33GHXe8yLRpc/jzn39H06Z5gCm/\nCKWyMli50iQdglVaYbOTDhCcpTM/+cRNbq553am0QkQkCrTxQvNt5rb6OjQ8xQlwpC+gJpIi/mpU\nReqrV6866fu4OOjQYTh79lR/GbRjx+PExq5g9Wrzfb9+A4iNjQ1mmBJh7L4OYGY7XHutpref6MUX\nb+fgwTYA/P73j1Xc36LFUW699Z88+eR9vPvuNWzZ0pNevb4NSUwbNzrJzzcn6sFqImlr186iVy8f\nW7Y4ycpy8ZOfBDYxYDeQ7NSpjISEyn3RqVwuJ0lJCeTmFlBWVvWVl3Dtv4qLi8nOXl/tzyM5dhGR\nWnMAyZ/AqttgyyUwvFFf42t49g8Aq3I2pfgnEMcCoOOBaNWokg67d4+nX7+T77vnnkn87nfz8PlO\nv0LpdJZx993X06qVqUfPzgZYzJAhQ4MfrESM5GQf7dr52LfPqaTDKQoK4vnrX38NwJgxaYwbt+Sk\nn99zz9M8++xdlJbG8OSTv+K5534Rkrjs0gowy2UG26hRpWzZEktGhunrEKimmfv2OVi82Pxfxo79\njr17T9+HnSopqer7w7n/ys5eX+X+91SRGLuISJ0kf2ySDgVt4ID2XQ3KnnMrbqqJpP+ys9dz2fPj\noW09BtkPn9yh44Fo1KiSDv36wbBTSsuHDZtP795TmDnzCTZv7l1xf3JyDk88MfO0BniHD4ciUokk\nDocpsXjnHSdpaW6gKNwhRYyXX57Ovn2mSdbvf//YaSfbXbp8x49+NJs33riB//znFh5++CHatDkY\n9LjspEOvXj7OOiv45VGjRpXx+uumr8PmzU569w7MlY9333VXrMBx8cV7q9yH1UY491/RHLuISK31\nWASOUrDc8J1WsWhQypMO7doV0LJlmGOJNm2BTuEOQsJB872AyZPns2nT2SxZMpbZs6exdGkKmzad\nHZaO+xKZUlLM7IYdO5xs366+DgBFRbH85S+/AeC881Zy6aULq9xuxoxZABQUNOG55+4MSWx20iHY\n/RxsJ/Z1COTSmXZpxdChZXTuXPXqICIiEoHic6FLprn9nfo6NCjlSYfk5PwwByISPZR0KOdwwNix\naUybNoeUlPSATY+WhsFuJgmQnt6oJghV67XXbuS777oA8OCDj1b7nhk4cD2XXWaWD/vHP37B8eNB\nXEoC2LXLwXffmV3b8OGhKYXp0MGiRw8zuyFQSYcNG5xkZ5ux1EBSRCQKJZevYrF/BHl5OnZoEEpj\nYN8AAJKT88IcjEj0UNJBxA9du1p07WpOKtPStHRmaamLP/3pdwAMHLiWiRM/rHF7e7bDgQNn8cor\nNwc1thP7OYRqpgOYvg5gkg5WACo67FkOsbEWkyYp6SAiEnWSTcIdy8WaNZqH3yB83w98polh796a\n6SDiLyUdRPxkl1ikpwfmpDKaffLJj9m6tScADzzwR5zOmp+QCy9cxJAhXwHw5JO/oqwseLue5ctN\n0qF1ax+9eoXuD2WXWOzb5+Tbb+s3Vaq0FN55x1wVu/TSUtWMiohEo/arocl+AL78UjvyBuGEJpKa\n6SDiPyUdRPxkl1js3+8kJ6fxvnXKyuCVV+4HoE+fjVx77TtnfIzDUTnbYcuWZL74YnLQ4rNnOgwb\nVhbSMqmT+zrUbxrtF1+4+P578xqbNk2zHEREopLTgl6m39GXX7Zq9BcsGoQ9Q8y/TXbRsqU+n0X8\n1XjPnERq6cS+Do25xCI9/Sy2b+8DwP33P47L5d9KDT/84Vy6ddsGwBtvzAjKwVdeHnz9td3PIbTL\nWHXqZNGtm3kuMjLq9/qwSyvatPFx4YVajktEJGqV93U4cCCeTZt02B317JkObb4KbxwiUUZ7PxE/\ntWtncfbZ5gQwPb1xJh18PnjrrW4A9Oy5heuue8vvx7rdZdx771MAZGcPZ8OG5gGP78svXfh8ZnpD\nKPs52OzZDllZdS/BOXoUPvrIzJS45ppSYmICFZ2IiIRcr8qVnRYtapzHDg2Gzwl7B5vbrVeHNxaR\nKKOkg0gt2LMdMjLc+Py7wN+gfPKJm61bmwLwu9/9Cbe7dif206e/TMuWhwCYO7dLwOOz+znEx1sM\nHBj6P5DdTHLPHifbttWttuP992MoKjKP1aoVIiJRrul+aG2uii9erBUsotoBD5Q2Mbc100GkVpR0\nEKkFO+lw5IiDDRsa19vHsuCpp0zH5rZtd3Ljja/VeoymTY9xxx3PA7B8eRu83sA+hytXmqTD4MFl\nxMUFdGi/BKKvw9tvm8f16VPGgAGNMLMlItLQdDGrWGRluTh+PMyxSN2d0ERSSQeR2mlcZ00i9TRq\nVCkOh5k3v3Rp43r7LF7sYs0ac1J/441/ITa2blfhf/nLvxMbWwjA88/HBiy+khJYtcrEF+p+DrYu\nXSy6dDGJgszM2k+j3brVwYoVJukwdWpJSBthiohIkHQ2fR2KihwsW6YSi6hlJx0SDkDizvDGIhJl\nGtdZk0g9tWoF/fubk8rG1EzSsuBvfzNTB1q1KuKqq16u81jt2u3niivMLIl589zs3RuYM+vsbCfH\nj4evn4PNnu2QmVn7vg52A0mn02LKlNJAhyYiIuHQNosmTcw+fdEilVhELTvp0OEr0EUBkVpR0kGk\nluwSi6wsFyWNpOQ+M9NVUbpw7bU7iY8vrNd411//NxwOi5ISB//6V2A6JdpLZYJZLjNc7L4Ou3Y5\n2bHD/6MSnw/mzjXPxbhxZbRvr7XVREQaBFcJgwYdAcysQYlCPgfsLV8us4NKK0RqS0kHkVoaO9ac\nVObnO/jTnyAz09ng195+8klTBtGqlY8JE/bUe7xu3TYxYsRBAF59NZb8/HoPWdFEsk+fMlq0qP94\ndXVyXwf/Dy5XrHCxY4fZJauBpIhIw3LeeaaJck6Oi507dZk86hzpAUXlq24p6SBSa0o6iNTSkSMO\nwGQZHnoIJk5MYPjwRFJTG+aUyRUrnKSlmf/b7beXkJAQmFkEP/zhDgBycx28/nr9ZjtYVuVMh3DO\ncgDo2tWiUye7r4P/rwm7gWTTphaXX67SChGRhsROOoBWsYhKJzaRVNJBpNaUdBCphdRUN3feGc+p\nxXzbtjmZPj2+QSYenn7a9HJISrL4yU+KAzZuv365FQmCl16KrVepyvbtDvbtM7uzcDWRtDkclbMd\nsrL8m+lQUAALFpjEy1VXldCkSdDCExGRMGjfvpBevUxCetEilVhEHTvpEJsLLb8NbywiUajhnSFJ\nrRUXF5Odvb7an7tcTpKSEsjNLaCsrOol/Pr1G0BsbOBWIogEpz4vlgX33z8cn6/qaZE+n4MHHrDo\n0GFVxaoD0f68rF3r5LPPzG7ipz8tJikpsOPfeWcxN9+cwO7dTt57z83UqaV1ej1+9lk7oC8ATZuu\npbi4d1if91Gjypg7N4YdO5zs3OmgS5ea628++shNfr550UydqlkOIiIN0fjxpWzZEktampuSEogJ\nTEsjCYWKJpKrwdnAa2pFgkBJByE7ez27d4+nX7+at6vuhDM7G2AxQ4YMDXRoYXXq8/LVVyns2bO0\nxsfs3t2E7dsfZMiQ9AbxvDz1lDlxT0y0uPXWwM1ysP3gB6X06uVjyxYnzz0Xyw9/WFqn1+PmzS8C\nfWnTZjc+30iys8P7vI8cWZk4yMx0MW1azYkEe9WKrl19jBgR3pkaIiISHBdeWMq//x1LXp6DVatc\n2t9HC4uTV64QkVpT0kEA6NcPhg2r++MPHw5cLJHkxOdly5aOfj2mefOOFY+J5udl27ZE/vtfczJ8\nyy3FtGoV+N/hdMLPf17Mr38dz8aNLhYvdtGyZe1fj5s2jQbgggsy6N8//M97jx4WHTr42LPHSWam\nu8akw759Dr74wky1nTKlBKeK3kREGqSRI8uIjbUoLnaweLGSDlEjtzMcP8vcVtJBpE50eCvip44d\ndwd0u0j31ltdAYiPt7j99uCtpjB1aglt2pgyieeeq31JxKFDLcnO7g/AmDHpAY2trhwOc3AJZ17B\nYt48d0XJjlatEBFpuBITqUg0LFqk635RY8+QyttKOojUiZIOIn5KSUmjV6/NNW7Ts+fmiDnxrY/t\n289myZK2ANxwQwlt2wavfjE+Hn76U3OynZbmJienaa0en5U1suL26NEZAY2tPkaPNgeW27c72bWr\n6j4gllVZWjFsWBk9e6pOVESkIRs/3sx8W7vWxfffa+nMqGCXVriPQ2tveGMRiVJKOoj4yeGAWbNm\n4HRWPx0yKSmX0tLov3rx6qu/xbIcxMZa3Hln4Hs5nOrmm4tp0sSccM+b16VWj01PHwNAYmI+gwev\nCXhsdTVq1Ml9HaqyYYOTjRvNzzTLQUSk4bvwwspjiCVLtIpFVLCTDu3XgkslMSJ1oaSDSC1Mnjyf\nefOmkJycc9L9zZrlArBmzbncfvuLWFF8wXrr1u589NENAPzoRyV07Bj8/0yrVnD99eake+nStuze\n3c3vx2ZkmH4Ow4cvx+2OnIOBnj0t2rY1ZSPVLZ1pz3KIi7O4+molHUREGro+fXx06GA+GxYvjv6L\nFI1CRdJhdXjjEIliSjqI1NLkyfPZtOlsliwZy+zZ01i6NIUDB1pzySUL1iwzJgAAIABJREFUAfh/\n/286jz76YJijrLu//OU3lJW5cTotfvnL4M9ysN12WzEul4XP5+Ctt+716zFFRbGsXGk6TkZaWYvD\nUVlikZFx+oFlSQm88465/7LLSmnRIqThiYhIGDgclSUWixe78FW9ErlEivy2kNfZ3FY/B5E6U9JB\npA4cDhg7No1p0+aQkpJObGwp8+ZNYdAgM73/oYce4cMPbwpzlLX33Xed+M9/bgHgoov20q1b6KZs\ndO1qcdVV5kBswYKfcuhQyzM+5quvzqWwMAGIrH4ONruZ5NatTvbsObl2d/FiFwcOmF3wtGma5SAi\n0liMH28+Gw4ccPLtt7XrYyQhpiaSIgGhpINIgCQl5ZGaOoHOnXcC8Mc//otVq8584hxJZs2aQXFx\nHA6Hjx/9aEfIf7/dP6KwMJEXXvj5Gbe3SyuczjJGjFgW1Njqwp7pAKf3dbBLK9q08XHBBZFTFiIi\nIsE1dmwpTqdJ6n/5ZRDWo5bAsUsrnMXQNju8sYhEMSUdRAKoU6fdfPTR5TRvfoSyshgee6wfGzZE\nx9ts3762/POftwJwySVv07lzQchjGDjQx+DBhwF49tm7KCyMq3F7u4nkwIHrSErKC3p8tZWc7OOs\ns8zc2ROTDkeOwMcfm9KKa68tJSYmLOGJiEgYtGwJQ4aYz4ZVq5R0iGh20qHtBnCHruRUpKGJjrMh\nkSjSv3827703Gbe7mOPH3fz4xwnVLpkYSZ588lcVpQq33PLHsMUxZYqZKbJ/fztee+3GarezrMqZ\nDpHWz8HmcMCoUWYWQ2ZmZV+H+fPdFBeb14RWrRARaXwuvNCUE2ZnJ0FxszBHI9XaW15eodIKkXpR\n0kEkCMaP/4I//MH0Rti718l11yVw9GiYg6rBwYOteP75OwCYPPldevUK3xTC8847RHLyOgD+9rf7\n8PmqTths2nQ2Bw6cBURmPweb3ddhyxYne/ea/8tbb5kERN++ZfTvry5iIiKNjd1MsqzMCbvHhzka\nqVJBCzjcy9xW0kGkXpR0EAmSH/zgTW655VsAvvnGxS23JFBUFOagqvHMM3eTn2+utDzwQPhmOYCZ\nHXD99X8FYNMmD++/f1WV29mzHCByZzpA5UwHgMxMJzk5sHKlKbWYNq0ER+RPghERkQAbMsRHixbl\nzZq/+0F4g5Gq7R1ceVtJB5F6iZqkg8fjecjj8fhO+fo63HGJ1GTatB3ceKOpAUxPd3PPPfFYoVsQ\nwi9Hjybx7LN3AXDFFakMHRr+D9ZLL51d0ZBz1qwZVW5j93Po2nU7nTvvCllsteXx+Gjd2sxmyMhw\n8frr5n6n0+Laa0vDGJmIiISLywXjxpV/Buz8AUTYsYFQ2c/BUQbt1oU3FmmUPB7PnR6PZ6vH4ynw\neDzLPB7PsBq2nezxeBZ6PJ79Ho/nqMfjyfR4PJeGMt6aRE3SodwGoB3QvvxrTHjDEamZwwF//nMR\nl15qDizeeSeGxx+PDXNUJ3vuuTs5erQFAL///WNhjsaIiSnhnnueBiAzczSZmSNP2ybS+znYHI7K\nEotPP3Xxwgvm/gsuKKNdOx1liog0VnZfB/J7wMHe4Q1GTmcnHdp8A7Ghb64tjZvH45kG/A14CBgC\nrAU+8Xg8bap5yFhgIXA5cC6wGPjA4/EMCkG4ZxRtSYdSr9f7vdfr3V/+dSjcAYmcidsNL71UwODB\n5sTzmWfiSE3tEOaojPz8RJ588lcAXHjh54wcGTnLTv7sZ/8iKck0wjh1tsP+/WexaZMHiOx+DjZ7\nCu133zk5cMDct369k9RUdw2PEhGRhuyk5ZK3XBa+QKRqdtJBpRUSHvcCL3m93te8Xu83wO3AceAn\nVW3s9Xrv9Xq9f/V6vau8Xu8Wr9f7AJADXBm6kKsXbUmH3h6PZ5fH49ni8Xje8Hg8XcIdkIg/EhPh\njTcK6NrVTLP/xz/OJi1tQpijgpdeuo2DB03C9MEHHw1zNCdLSsrj9ttfBGDBgqvxes+u+Flm5qiK\n25GedEhNdfPmm6evifn9906mT49X4kFEpJHq0MGiR498881m9XWIKEWJcMBc3FDSQULN4/HEAEOB\nz+37vF6vBXwGnD79t+oxHEAzICIu0kdT0mEZcDNwGSbT0wNY6vF4EsMZlIi/2ra1mD37OC1bWvh8\nDh544G1Wrjwv5HFYFixdmsJrr93A44/fD8Do0emMG7ck5LGcyd13P0NMTDGW5eRvf7uv4n67n0NS\n0lH6998QrvDOyLLg4Yfjql2Bw+dz8MgjcRHX50NEREJj6NDy84FtF0BJXFhjkRPsG0jFaZKSDhJ6\nbQAXsO+U+/dhWgz4YwaQCMwJYFx1FjWX2Lxe7ycnfLvB4/GsALYDU4H/hCoOl8uJ2316rqa4uJgN\nG9ZX+zin00HTpvHk5xfi81V9htG//wBiY0+v93e5ApMbqi72QIwfzLGDPX4ox+7TB/7v/wq5+uo4\nCgsTmTjxQ7KyRtKz59aAjH/i/VV5771JzJgxiy1bkk+6f/z4RaetohAJf9OOHfdw/fX/xyuv3MJr\nr93Io48+SLt2+yv6OYwcmYXLdfqSk+F4vVQlM9PJtm01b7t1q5Mvv3QzcmTNS2dG+ms92OMr9tqN\nHezx9ZnX8F6P/jyurjFE8/MS7NjPP/8I8+Z1hZJE2DEGen1exaPrNnZjf97rNbZdWgHQfk3gxz+D\nur5PT/z94Xqv6vUYfh6P58fAg8BVXq/3QLjjgShKOpzK6/Ue9Xg8m4DkM24cQElJCbRsefrkipUr\nv2bnznH061fz45s2rfr+7GxISlrBsGGnNyVNSkqoS6hVjlNV7IEYP5hjB3v8UI99+eXwyCObuf/+\nnuzf347LL/+IzMxRtG5d+9lPtYn9vfcmMWXKPHw+12k/e/zxBzj33NVMnjy/TmPXhb/j//rXf+WV\nV26hqCiev//9lzzwwB9ZtWooUH0TyXC8XqqSl+ffmHl5CbRseebfW1+R8jeNtLGDPX64Xo/BHH/l\nyq+5+O/joG0dB94PKx7QZ144xq/NPqy6x4fiMdWN09D+pqNGFYP7GJQmmr4OdUg6NMTXY1jHtoCc\ny83tZjshLjew4/uhvu/TusYR6X/TYI8f7Nhr4QBQhllA4UTtgL01PdDj8fwI+Ccwxev1Lg5OeLUX\ntUkHj8fTFJNweC2Uvzc3t4DDh49VeX+/flDF8VNAxk5Kqvu4oRhfsddu7GHDdnP33c/x9NNPsWmT\nh6uvXsCnn15CQkJhQMY/NXbLghkzZlWZcADw+VzMnPkEkybNr5jxECl/0379vmbChA9JTZ3Ic8/d\nQVLSUUpKzNXRUaOq7ucQjr9pVZo1cwJn/qBq1qyAw4drnukQ6a/1YI+v2Gs3drDHz80tMAmHTkEa\nOwCCOX5DjP1MXC4nSUkJ5OYWUFZW8/6qqt8ZCA3xb1pYeBw6LIadE01fh0tnBmzsGmO3gO0pkNcR\nmu2GbmlQdSVg1D7vdRp74yRYOAsOl1/TzOsCz+bApTOg7/yTNo3E9ymE/73aEPePgYrdX16vt8Tj\n8awCLgLeh4oeDRcBz1b3OI/Hcx3wb2Ca1+v9OBSx+itqkg4ej2cW8AGmpKIT8DBQArwVyjjKynyU\nlp7+Bq7tmzrUYwd7fMVe+7F//OOnsaxuPPPMPWRkjOHGG1/j7ben4XT6X+Dvb+xpaSmnlVScavPm\n3qSnjyElJb1WY9dVbcafMWMWqakTOXKkFb/5zayK+3/2s3/z17/++qQZGrUdO1BxV2XYMB/du/tq\nLLHo0cPHeeeVUlp65t9bX5H0N42ksYM9frhej9Eae2P/mwZ7/NrswwL1+Gh+XkISe+dPTNJh/wDI\n7QhJuwM3dlVOPbEGaLm5yhPrOo1fCxE19sZJMGceWKdcoDmcbO6fOuWk5yeS36d1HSPS/6bBHj/Y\nsdfSk8Ar5cmHFZjVLJoArwB4PJ4/AR29Xu9N5d//uPxndwErPR6PPUuiwOv1Vj1dJ4SiqUClM/Am\n8A0wG/geGOH1eg+GNSqRevjb3+7jmmveAWDevB/y61//NWBjHzjQjnfeuYb77vsr06e/7Ndjdu/u\nGLDfH0gHD7bCXJY52bff9mLKlHm8996k0AflB4cDHnqoqNpEktNp8Yc/FJ3WT0NERBqRLidckNwc\n5KUz7RPrw6dciLBPrDdG5udp0FmYRMypCYeKn7vg0yeqOhQRCQqv1zsH+DXwCLAaGAhc5vV6vy/f\npD1w4kqOP8M0n3wO2H3C19OhirkmUTPTwev1XhfuGEQCzeXy8cYb/8PFF7cnM3M0Tz31K7p1285d\ndz1LWloKu3d3pGPH3aSkpNV4YlpWBl6vkxUrXKxY4SIjYzh79tRY8lWljh1rd3UlFCwLZs6cRXXz\nPqsqDYkkEyaU8vLLhTzySBxbt1bmeXv08PGHPxQxYcIZpjiIiEjDlrQZWnwLR3qavg7nBqk/ur8n\n1n3mV1tq0WBtTzk9EXOqQ71Ns89uVfeTEgk0r9f7PPB8NT+75ZTvx4ckqDqKmqSDSEOVkFDIggVX\nM2pUJjk5Z3PPPU/x5z//lr17O1Rs06vXZmbNmlFRRpCfn8iKFcNZvrwbf/5zAl9+6SIv78QjhJiK\nW0lJRxkxIosvvxzGoUOtq40jOTmn2saM4VSX0pBIM2FCKVdcUcrKlW7y8xNo1qyA884rjcgkiYiI\nhJgDSP4YvrwDtlwCPic4gzCdWyfW1cvzc6anv9uJyEmUdBCJAG3aHOSjjy7n3HNXkZvb4qSEA8CW\nLclce+07/OAHH7F3bwfWrh1UbVPIbt18JCfv57zz/pfrr8/gnHO+xuXy1bh6hdNZxhNPzIzIk2B/\nSz4itTTE5nDAqFE+WraEw4d9Z+zhICIijUjyJybpUNgKdg2DLssD/zv8PWFeeTsk7oM2OYGPIVI1\n83Omp7/bichJlHQQiRA9e35LUlIeubktqvy5ZTn56KMJJ93ndvsYNMji/PPLGDbMfLVrZ7F69Te0\nbPkSAwZUbjt58nzmzZvCzJlPsHlz74r7k5NzeOKJmac1Y4wU/pZ8RGJpiIiIiF96LAJnCfhizCoW\nwUg6+HvCvOF683XWBuj8LpsHN2XwYCLywkTAdEszy2Pmdal+m1Y50LWRzQARCRAlHUQiRFpaCt99\nV8OHXbnRo9O48soPadUqg/btH2fEiCF+/47Jk+czadJ80tJS2LOnAx077mbMmPSIPpBISUmjV6/N\nNZZYRGppiIiIiF/i8qFLBmy/wPR1GP9wYMcvc8PX15x5O3cBlMYBTvi+P3zfnzvvhL/8xccVV5Qy\nYUIpw4aV4YymVvT+KI0Hq4aDIUcZXDKz8fW6EAkQJR1EIoS/5QG//OU/mDZtDitXmmn6teVwwNix\nabV+XLg4HDBr1oyoLA0RERHxW/LHJumw63w43hKaHA7MuLkdYO4c2Dmm/A6LKs+eHWVw7Y+h8zL4\n5mrYeA1sHQ9WDDt2OHnxxVhefDGWtm19XH55KR5PS/C5gSrqBS1MD4m8jmaGRbe0yD5hX/QY5Hc2\ntxP3wbF2lT9rlWMSDlUsJyoi/lHSQSRCqIygetFaGiIiIuK35E/g8z+bVSS+vRj6z63/mHvGwptv\nw7H25vsen8HA1yHt96ZppO3UE+thL5mvb1swo10mGzYks3ixm8JCB/v3O3n11VhgEMTuhz4fQN93\noddCiC0wy24unHVy08qWm+HSGZF54r59NGTda273ToXrJsKOFMjvYBImXdMjO2EiEgWUdBCJECoj\nqFk0loaIiIj4rd1aSNxrEgSbf1CvpINlwbx5nSH1c7DKD/fHPA4XPmhWxhj8mpmJcKYT67gjXHzx\nPmbM6MyxY7B4sZvUVDcLF7rNqlnFLWHdjeYr5hi0XQe7hgOn1F8cToY582DqlMhKPBQ3gQX/AZwQ\nfxiuvNWE3j16ZoSKRAMlHUQihMoIzizaSkNERET85rTMbIF1N5q+DtVUQZxJfj7cfXc8H3xQfhEj\n7ihMvhH6vF+5kYNan1gnJsLEiaVMnFhKcTG88spWfv9GFuycZMoRShJh18jqB7Bc8OkT0Gd+5Mwc\n+Pzxyhkfl98FSY1vNqlIKDS0NjAiUc0uI0hOPnmZquTkHObNm6IyAhERkYYs+WPzb14n2N+/1g/3\nep1cemkTPvggxtzRah3cOvTkhEMAxMbCsGGHIOV2uK8j3JIC58w58wMP9YYdY868XShsGwvL7za3\nPfNh4BvhjUekAdNMB5EIozICERGRRqrXp4APcMLmy6DdBr8fumCBm7vvjuf4cXPAcNFFe/m86who\nXRCcWG1OH3RLh9xO8PXUM2+f51/j7KAqSYT5/zG3Ew7CxNsjZ/aFSAOkpINIBFIZgYiISCOUeAA6\nroLdw0xfh9F/O+NDSksdPPhgHC+9FAtATIzFo48WMXjwN3z+TpATDidq5mdpgr/bBdPyJ+BIT3P7\nijuh2b7wxiPSwKm8QkREREQkUvT6xPy7I8U0OqzJ8fbMnDmoIuHQsaOPBQuO85OflIR+hmS3NLNK\nRU1afGuaVobRV1+1hI13mG/6zoP+b4c1HpHGQDMdREQCpLi4mOzs9dX+3OVykpSUQG5uAWVlviq3\n6ddvALGxscEKUUSkStp/RZDkj82SlmVxsO0COPu/VW+3fQy8O4fsghYApKSU8tJLhbRpY4Uu1hM5\nMMtizplnmkZWxVkCJQlmac0wyMuDp57ymG+afA8T7oiqsoozvU9B71WJTEo6iIgESHb2enbvHk+/\nfjVvl5RU3eMBFjNkyNBAhyYiUqPs7PVc9vx4aFvHAfbDJ3do/xUQnZebFSeKmpu+DqcmHSwg616z\nEkT5cph33VXEb39bjDvcR/Z955tlMT99onJVCDDLURa2hEMeeOdNmHYtpndFaP3v/8axf3/5yfbE\n26Hp9yGPoT7q/T4FvVclLMK9axIRaVD69YNhw+r++MOHAxeLiEittAU6hTsIwVUKPT+DjdfCxsnQ\nJdP0QeiWBsVNYcHLlQ0bY47y0P07uPPO7mEN+SR955tlMbenQH4HE3vnDHj3LcieBt5J8NEzMOiX\nIQ1r0SIXr79ennDo9Rac825If3/A6H0qUUhJBxERERGRSNKkvLFhXhd4Z7a5nbTdlC3kdTbft10H\nF1zLqFH/ArqHI8rqOYDupzTEnnQT5LeH7eNg5S/AsR1+GJpwjh6Fe++NB6Bly2IOj/pFaH6xiABq\nJCkiIiIiEjk2ToKvbjv9/txulQmHga/DT0dC8zM0bowkMUUwbTK0+dp8v2IWixfXp07Afw8+GM+e\nPea05667vBB/KCS/V0QMJR1ERERERCKBBSycVX0jRoAm+2HSjRB7PGRhBUyTw/A/l0PTPQD89a99\nyMio4f8aAAsXupg9OwaAKVNKGDXqYFB/n4icTkkHEREREZFIsD0FDifXvM3xtrBzTGjiCYYWO+D6\nKyAmj9JSJzfdlMA33wTnlOTwYbjvPlNW0a6dj8cfLwzK7xGRminpICIiIiISCfI6Bna7SNVhDVw0\nBafTIjfXwXXXJbB3b+DXrrz//nj27TOnO08+WUiLFgH/FSLiByUdREREREQiQbPdgd0uknVZyD33\neAHYtcvJddclkJcXuOEzMtrwzjumrOK660q45JKywA0uIrWipIOIiIiISCTolgYtz9AcslUOdE0P\nTTxBdtlle5kxowiA7GwXt9ySQHFxAAYubM2zz54NQMeOPh55RGUVIuGkpIOIiIiISCRwAJfOAEc1\nV+UdZXDJTLNdA/HrXxfz4x+bTMPSpW5+9at4LKueg2b8gyNHYgFTVtG8eT3HE5F6UdJBRERERCRS\n9J0PU6eYGQ0napVj7u87PzxxBYnDAbNmFTF+fCkAc+bE8Npr3es+YPYU+PZHANxwQzEXXqiyCpFw\nc4c7ABEREREROUHf+dBnvlnNIr+D6eHQNb1BzXA4UUwMvPxyAVdf3YT16128+WZ3SPkpdPp37QbK\nPwtSnwegXbtCHn64JPDBikitaaaDiIiIiEikcQDd06D/HOjWcBMOtqZN4c03C+jSxWfuSH8BNl3u\n/wAW8OGLcPwsAO699xuaNg18nCJSe0o6iIiIiIhI2LVrZ/HWWwU0bVoClhvmzoVdQ/178IYfwTfX\nmNvnPMeQIUeCF6iI1IqSDiIiIiIiEhHOPtvH//7vBnAWQUkivJkKh7vX/KC89pD6nLnd4ls4/zdB\nj1NE/Kekg4iIiIiIRIwBA47CBTeYb461gzc+guOtqt7YAj54CQrLfz7pFog5FpI4RcQ/SjqIiIiI\niEhk6TUXLr3P3D7YB956H0riT99u7Q2w6Spze/jT0H1p6GIUEb9o9QoREREREYk8I5+Eo11h+d2w\nczS8+zpMmWZu53UEVzH891mzbascuOj+8MYrIlVS0kFERERERCKPA7jsV5DbGTZeCxunwBMHoajF\nKRv6YNLNEFsQhiBF5ExUXiEiIiIiIpHJ6YNr/gdabzTfn5ZwKHesbehiEpFaUdJBREREREQil7sQ\nyuJq2MAJnz5hmkqKSMRR0kFERERERCLX9hQ40rPmbQ71hh1jQhOPiNSKkg4iIiIiIhK58joGdjsR\nCSklHUREREREJHI12x3Y7UQkpJR0EBERERGRyNUtDVpurnmbVjnQNT008YhIrSjpICIiIiIikcsB\nXDoDHGXV/LwMLplpthORiKOkg4iIiIiIRLa+82HqFDOj4UStcsz9feeHJy4ROSN3uAMQERERERE5\no77zoc98s5pFfgfTw6FrumY4iEQ4JR1ERERERCQ6OIDuaeGOQkRqQeUVIiIiIiIiIhIUSjqIiIiI\niIiISFAo6SAiIiIiIiIiQaGkg4iIiIiIiIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiISFAo6SAiIiIi\nIiIiQaGkg4iIiIiIiIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiISFAo6SAiIiIiIiIiQaGkg4iIiIiI\niIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiISFAo6SAiIiIiIiIiQaGkg4iIiIiIiIgEhZIOIiIiIiIi\nIhIUSjqIiIiIiIiISFAo6SAiIiIiIiIiQaGkg4iIiIiIiIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiI\nSFAo6SAiIiIiIiIiQaGkg4iIiIiIiIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiISFAo6SAiIiIiIiIi\nQaGkg4iIiIiIiIgEhZIOIiIiIiIiIhIUSjqIiIiIiIiISFAo6SAiIiIiIiIiQaGkg4iIiIiIiIgE\nhZIOIiIiIiL/v707j5OjrPM4/snFuSI34RZEf7DsC5AgCKjLEUBQIoLIIYrgRYiwBlhgJcsVkdMA\nCigKGnAFuRNAIMgV5FAkHKtgfgIBooAgQpbTkJDZP37VpqbTPZOu6md6aub7fr3mBd1V8+1ferqq\nnn7qqadERCQJdTqIiIiIiIiISBLqdBARERERERGRJNTpICIiIiIiIiJJqNNBRERERERERJJQp4OI\niIiIiIiIJKFOBxERERERERFJQp0OIiIiIiIiIpLE8E4X0CozGwccBYwEHgUOc/ffdbYqERERERER\nkfZo9XuvmW0HfBfYGJgNnOLul/RBqb2q1EgHM9uHeCNPAD5EvPnTzGzljhYmIiIiIiIi0gatfu81\ns/cBNwK3A5sC5wIXmdlOfVJwLyrV6QCMBy5090vdfSZwCPAWcHBnyxIRERERERFpi1a/944FZrn7\n0R7OB67OcjquMp0OZjYCGEX03gDg7l3AbcDWnapLREREREREpB0Kfu/9SLY8b1oP6/epynQ6ACsD\nw4AX655/kbjORURERERERKTKinzvHdlk/eXMbMn2lte6yk0kWcZjj5X//bXXHsrw4Yv21QwbNrRU\nfsrs1Pmqve+zU+er9tazU+f35+zU+aq99ezU+cOGDYWXimfzUmQkyU6dr9r7Pjt1vmrvTH5Vs1Pn\nq/bO5CfOHuyGdHV1dbqGxZINM3kL2Mvdr889Pxl4r7t/plO1iYiIiIiIiJRV5HuvmU0HZrj7Ebnn\nvgSc7e4rJC+6F5W5vMLd5wEzgB1rz5nZkOzxfZ2qS0RERERERKQdCn7vvT+/fmbn7PmOq9rlFZOA\nyWY2A3iAmI1zGWByJ4sSERERERERaZMev/ea2anAGu5+YLb+D4FxZnY68BOiA+KzwG59XHdDlRnp\nAODuVwJHAScDDwObALu4+986WpiIiIiIiIhIGyzG996RwNq59Z8BPgmMBh4hOim+7O71d7ToiMrM\n6SAiIiIiIiIi1VKpkQ4iIiIiIiIiUh3qdBARERERERGRJNTpICIiIiIiIiJJqNNBRERERERERJJQ\np4OIiIiIiIiIJKFOBxERERERERFJQp0OIiIiIiIiIpLE8E4XICIiIgOXma0GfN3dTy6ZsxYwx93f\nqHt+BLC1u99dMHclYBPgUXd/xcxWBr4MLAlc5e5/LFN3g9ebBezi7k+0OXcIsB2wAfACMM3d5xXM\nWgv4h7u/nD3+GHAIsA7wLHC+u99fotYjgavd/dmiGb3kfwrYkngP7jWzHYCjiJNt17r7j0rmLw3s\nB3wUWB1YAMwCprj77aWKj/wtga2BkdlTfwXud/cHymb38JorALu7+6Ulc4a6+4JGzwNrufvsgrlD\ngPcBf3b3+Wa2BPAZYju9qfZZbSczuwM4qN2fUzNbj2w7dfc/lMxaElhQ29bN7P3AwSzcVi9296cL\nZu8F3Ozub5WpsYf8TYFRwF3uPsvMNgbGEdvpde4+rQ2vsQOLbqfXt2P/24nttMqGdHV1dbqGfkmN\npEVeT40kNZJ6y1cjadHfVyOpcZYaST2/xoBqJGXv2UPuPqzg768OTCXe9y7gMuDQ2nE1O14/XyQ/\nez9uBZYD5gA7AVcB84m/6RrAR939oQLZhzdZNAk4g3jvcffvtZqd5d8E7Ofu/2dmKwI3EceQl4GV\ngD8BH3f3vxXI/i0w0d1vNLNPA9cCNwJ/BD4IfArY091vLFj7AuKUkqpEAAAZy0lEQVSzfSdwEbHt\nvFMkq0H214HzgEeBDxDb5wXAFcC7wBeB/3L3cwvmbwDcBiwNzAXWIt77lYEtiPdqf3efXyB7VeAa\nYFtgNvBitmg1Yv94L7CXu79UpPZeXrvsdroc8bfcHXgNuBA4yd3fzZaX2U4NmAasTewPdya20w2B\nIcBbwDZF95FmNqbJomuB/wD+DODu1xfIvgA42t3fyNphPyPaAUOI/dl0YEz994QW8u8CznP3q81s\nW+B2wFm4rRowukj7N9tOXye2nYvd/bdFamySvSdwJbHfXZJ4T64CHiS209HAF939soL5qwI3ENvk\nAmJ//jCwJrAKMMndjy6R3ZHttMo00qG5kcAJQKFOh/pGkpl1ayQBKxIH29KNJDOrbyQda2btbiSt\nAxxkZskbSWZWqJFE7AAmAvWNpHuJHe90MyvcSALOBE43s9SNpP8ws/pG0jlmtnSCRtKHgbFmlqqR\ndLaZpdz5rgP8FCjU6ZBvJJnZIo0k4sD0NMW2026NJDNbpJFkZikaSR8HPmVmyRpJZlaqkUS8L+cB\njRpJuwHjzaxQI4l4j183s+SNJDOrbyT90sxSNJL2JPY9qRpJpbZTM9ukt1VazaxzGvF+bAUsnz2+\n08x2dvdXs3WGFMw+hfgbHgF8HZgC3OLuXwUws58A/018/lt1DvAccWzOG0p88Z1HfOkodDwFPkE0\n1gG+DbwHeL+7P511wk8h2jBjC2RvDDyW/f9/Ad9y99NrC83sG1l20eMpwFeAPYj9y2tm9j/ARWU7\nNYHDgbHufpGZbU8c64509wsAzOw3wNFAoeMp8fe6JXuNLjM7Bvh3d/+ImX2AaJ9NAE4skH0BcbzZ\nyN09vyA7pvwEOB/Yu9Xg7HjXk/e0mllnIrAp8AViO50AbJ61u2ptpaLb6elE+2h3ooP6l0Sn2tbE\n9nQVcHz22kVMIbbFRvV9P/tvFwXaAsR+5UTgDWJfshWwI/AA8CHgEuA4Yjsr4kPEewOxP7vA3Y+o\nLTSziUT79aMF888i9n9fMbPHiTbTz9z97wXzao4DTnD3U8xsX+JvOMndJ2Z1Hwn8J9HJXMT3gOeB\nFYh271nAcu6+Rdaxf6WZPVewXZ1sOx3IBm2ngxpJTamR1DM1khalRlJjaiQ1p0ZSY1VtJD1C889i\n7fkywypHA59x9wcBso6qq4A7zGzH3OsUMQo43N1fN7Nzie32x7nl5wEtd9xlfkRsO/vnRx+a2Txg\nZ3d/vGBuIzsQHYVPA7j7X7L9/I97/rWm5rNw/7oecHPd8puJ96qMm9x9ctYh9iXgIOAwM5tB1P0L\nd3+9QO56xDENd7/TzIYB+VGldxGf9aL+HdjM3WufubOBiWa2krs/YWbfJNpSJxbI3oUYneL1C9zd\nsxNDdxUrmzn0vJ2U3U73AA5097sAzGwKcdy7IddJXjR/G2Kb+b2ZTSBGH3wtN1ruNODyErVPIzqO\nD853vGbb6qYlt9X8fnF3Yju9K3t8r5kdQRzvih5Ph7HwOL8h8d7kTQa+WTAb4EJ3n2hmo4gR1ScA\np5nZ9cCP3f1XBXMN+Hn2/1cQJ4+m5JZfR7FtqGZXYvTLawBmdizwqpkd5u53ZNvpBIq1q1NupwPW\nYJ5I8hHiDNIjDX4eBn5RMn800ZB50N1vI84uvUA0klbM1inTSJqUHYzPJYZ/1jeSPlww+0fEqIPd\n3H292g+xM945e7x+wex6OxBDHP/ZSAKOITbmIhankVS2M+kmd9+DGClwBlHro2b2gJl91cyKfgnu\n1kgiDiD1jaR1C1cdjaTv1jWSRtcaScQB6cCC2bsA45rtfIkOlU8UzJ4DvNrDT6HLk3L2IC6jutrd\nLyLOMK9CNJJqnWNlGkknuPvviQPbhsBZ7j7P3ecSHZEfL1H7NOIzPdLdh9Z+iG3137LHhYbJ0qSR\n5O5vufu9RIfnniVqr28kXVK3fDLRGVTUhe6+ObEfvJtoJD1nZldmI8OKqm8kLcuijaQNSuTvCkxw\n99eyz8ixwH5mtpy730Fsp0U6ZCHtdvoK8FViP1b/sz4xFL+M9xLbOwDZe7Mn8AwxYnDVEtlLAG9n\nufOIYdr5y55qo/Ba5u6HEB3d07JO7xRq+6cVgKfqlj1JtA+KmE5cjgfRJtqubvn2xAmK0tz9JXc/\nw903yl7nceIY9ULByL+THS/NbA3iBNs6ueXrEp/ZoubQvcN7mew1ah3V/0tcGlXEXGIUazPvydYp\n4nXii+0OTX6+VjC3ZhXi8jgAPC4fHE3UfBPxPhX1L2R/M3d/E3iT7p+PPxOjtgpx912JEXcPWlzq\n2m617XQk8fnIe5QYEVnUb4njNMQ+oP7YuRnlPu8AuPsMdz+U+Gx/lfh732JmhS6FJD6PtX3r8sQ2\nlN/XrkSc+ChqLt3bbwuIdkfthPt9xOWvRbNTbacD1qAd6UBsgEcTO5lGNiaGuRa1SCMpG5p7FdFI\nOqBEdrdGkpm1tZGUDRmeZmZnuPt5JepsJnUj6X9Z2EjK79zb2kgiOh3OsJg74stEI+ls4uDYqloj\naXZdI6k2gmIwN5JOIQ6qjXyAuCSiqEUaSWY2mvhCfxMxsqWobo0kM2t7I8nMxhONpEO9+GVDzfRF\nI2kmCxtJj+aWt62RBMzIziTtTYw4ucXMZmedqa2qNZKeQY2kvBnAGt5kHhEzW57iI4YgruHeBPjn\npUgec6TsTRxTy3z2/0x0jDyTPd6X7tvp6nQ/vrbE3a8zsweAS83sk8TZ/HaabGZzgRFEJ89juWUj\niX1/EccCv86OR/cAp5jZh4lLoAzYh5gzqaiGnbnu/uvsdQ/PXqOIqcDFZnYJMIY4g/pdM+siOmXP\nIuvkL+hXwCQzO4TYZk4FHsmNylgHKHo54RXAJdm+/fbcWdrliNFmkyh+Rv8hAHef3mihmc2h3HY6\nG9iIuCSR7LVezy4tvJXolC3qeeJ9rc2vdDTd3+NVyLW5i3D3sy0un/25me0OjC+TV2di1lZfQLRx\n89vpSkQnSlETgJvNbFnis/HdbARrbVs9nPiMFrHIduru/yBG+/7M4tLdovu024Dzzez7xLZ+K3Cq\nmR1MbKdnEvueou4BTjazA4m27neAWe5ea1uU+cyk3E4HrMHc6aBGUhNqJDWlRlJjaiQ1pkZSc2ok\nNVbVRtIPiVEfzcym3HHkZuIs7DX5J3PH1GuI0WdF/ILcSAl3/2Xd8jHEZUWFuftzWWfmsUSHeJl9\nVl5+hNBUFj2TvBcxerNl7v5HM9uKuAzyaOLv+3liROHvgH3dfUoPEb3p8T3IPp9FLw05hjg5sy/R\nUXcYsU+ZQrQ7plN8KDvE+zGVGJHRRbTJ8pezrkLsC4o4ghiF/AtguJnVTgwsQbz3FxMTTBdxGTGv\nUzN/BU4qmA2xPzyI6LD/J4+5gXYh2iFF3UaMirsny/xB3fKdydoLZbj7I2a2BXEC6RHas63ezcJR\nto+z6KjV3eh+fG2Ju99vZrsS+/CtsqePy/77PHCiF5wPjN630ydzr9Wqo4jj8g+Judf2IfY3jxHb\n1VPECb2ijiI+k7XLit6k++WDGxGjKotIuZ0OWIO500GNpB6okdSQGkmNqZHUmBpJTaiR1GN+5RpJ\n7t5j55zHPEb1l9C04jiaDM3Ojql7ETOSt8zde9t/nEJ0KJWSXdp2qpndSsxVUvTSgXxmb22UkyhR\nu7s/RVzeM4RocwwFXvaCd5iqy052eW82/L7+UoGzzOw8YIQXmycin/8SsHXWUbokMNNzkzC7+9Ul\nsucSkzsfQ1xKm7/LzIxaZ2HB7B7bJ+7+IuWOpyfQZKRq1pm/E7B5keDsUqWeXEG5fUz+td4GDsnm\nodieEifxsrztelnlMorv12uvcT/xmVyFOCk5lLjT1DNlcokTg0Umdu9V9nnbue7pw8zsbGJ/3227\nKpA/y2L+vm2J7fQ3nrtjmLtPLpGdbDsdyHTLzETMbDiwTLMPXrZ8zWYjLUq+9jLAu9lG0Y68UUQj\n6VJfOAlmEtmZz3ezM5NlctreSOoEM1uKNjSScnkNG0ltyl6Oiu18LW65uYa7N/wCnc3RsXmzkRYl\nX3s94havpb985DJrjaRTPeGtmsxsfeAdj3lYyma1tZFkZusCs33h/CXJZe9H6UZSlrUMTRpJ7dAf\ntlOLO8Vs5u6zqpZf1ezU+aq9c/kiIlWgTofFVOWDUlWzU+er9s7li8jgZWavEzPCp9p/Jcuvanbq\nfNXeN/lmthox+XGh27l3Kjt1vmrvTH5Vs9uVb3HXvTled/twMxsBbO3uZSc7H1AG890rWtWuyws6\nkV/V7NT5qr0P8s1sNTM7vl15fZWdOl+1dya/qtntyjeztcxskcluzWyEmZW5m4qIpDeSuIyhatmp\n81V7Z/Krml0q38xWt5j77llgjpldWndcXZG4aYDkDOY5HUSkb9R27Cl6q1Nmp85X7Z3Jr2p2qXwz\nW52Y12UU0GVmlwGH5s7Q1BpJRW+zKiIlZdeg97hKf8xOna/aO5Nf1ew+yD+NmGR7K+JOVqcBd5rZ\nzrnL0FOfHKwcdTqISCk6KPV9dup81d732X2Qr0aSSP/3CDGJbKNtsfZ80euiU2anzlftncmvanbq\n/NHAZ9z9QQAz25a4M+EdZrZj7jUkR50OIlKWDkp9n506X7X3fXbq/P7USEr9Oinzq5qdOl+1tyf/\nFeJuU7c3Wb4xcEPBOlJmp85X7Z3Jr2p26vz3krt9tbvPNbM9iWPqncABBXMHNHU6LL7+dFAaLNmp\n81V7e/J1UOr77NT5qr3vs1Pn96dGUmXmpBlA2anzVXt78mcQd1RqeGczM1u+xby+yk6dr9o7k1/V\n7NT5s4BNgCdqT2S3b96bOKbeWDB3QFOnw+LrTwelwZKdOl+1tydfB6W+z06dr9r7Pjt1fn9qJO0K\nPFfR/Kpmp85X7e3J/yGwbA/LZwMHFawjZXbqfNXemfyqZqfOvxn4GnBN/sncMfUaYK2C2QOWOh2a\nMLO1gZPc/eDsqbYelFLmVzU7db5qT5avg1LfZ6fOV+19n506P2kjycyWJiapfMXdH69bthTwOXe/\nNHvNe/pTflWzVfvAq93dr+tl+avAJa3Wmzo7db5q70x+VbP7IP84YJkmufPNbC9gzYLZA9aQri7N\nc9GImW0KPOTuSWbyTplf1ezU+aq9c/ki0llmNhxYxt1f62H5ms1GWfSS/UHgVmAd4tKse4B93f2F\nbPlqwPNF9y8p86uardoHZu0FankN2MzdZ1UpO3W+au9MflWzU+enrr0qBu1IBzMb08sq6/fX/Kpm\np85X7Z3Lb0WVd+yqve+zU+dXNbvVfHefDzTscMgt/2eHQ4u1nw78AdiCuDPGOcC9Zradu89ejN/v\nZH5Vs1Pnq/bO5bdisFzG2Z+yU+er9r7PTp2fuvZKGLSdDsAUms8SXlNmGEjK/Kpmp85X7Z3Lb0WV\nd+yqve+zU+dXNTt1fivZ2wCj3f1l4GUz2x24APi1mW0PvFmylpT5Vc1W7QOzdhGRAWkwdzq8ABzq\n7lMbLTSzzYhJvfpjflWzU+er9s7li8jgtTQwv/bA3buAsWZ2HjAd2L8f51c1O3W+au9cvojIgDO0\n0wV00AxiEqBmejsr3Mn8qmanzlftncsXkcFrJjHUvBt3/wYwFbi+H+dXNTt1vmrvXL6IyIAzmDsd\nzgTu62H5k8D2/TS/qtmp81V75/JFZPC6Dtiv0YLsi9jllOvUTJlf1ezU+aq9c/mtSHlZZOpLLlV7\n32enzq9qdup83bUB3b1CRPrYYJm4rz9lp85X7X2fnTpfs22L9H9m9jqwaaJ9QLLs1PmqvTP5Vc1O\nnZ+69qoYzCMdRKQz+svkd/0tX7V3Jr+q2anzdbmVSP+3K/BcBbNT56v2zuRXNTt1furaK2EwTyQp\nIn3AzNYGTnL3g7On2rbzTZmdOl+1dya/qtmp81PXLiKLx8yWJuZgesXdH69bthTwOXe/FMDd7+kv\n2apdtfen7KrXPhBppIOIpLYicGDtgbvf4+5zK5CdOl+1dya/qtmp81PXLiK9MLMPAn8E7gZ+b2bT\nzWz13CrvBX7a37JT56v2zuRXNTt1furaByqNdBCRUsxsTC+rrN8fs1Pnq/bO5Fc1O3V+6tpFpC1O\nB/5A3B1jeeAc4F4z287dZ/fj7NT5qr0z+VXNTp2fuvYBSZ0OIlLWFHq/5WbRGWtTZqfOV+2dya9q\ndur81LWLSHnbAKPd/WXgZTPbHbgA+LWZbQ+82U+zVbtq70/ZVa99QFKng4iU9QJwqLtPbbTQzDYD\nZvTD7NT5qr0z+VXNTp2funYRKW9pYH7tgbt3AWPN7DxgOrB/P81Ona/aO5Nf1ezU+alrH5A0p4OI\nlDWDmEynmd7OrnYqO3W+au9MflWzU+enrl1EyptJDNnuxt2/AUwFru+n2anzVXtn8quanTo/de0D\nkjodRKSsM4H7elj+JLB9P8xOna/aO5Nf1ezU+alrF5HyrgP2a7Qg+0JzOcU7B1Nmp85X7Z3Jr2p2\n6vzUtQ9IQ7q6dAmniIiIiIiIiLSfRjqIiIiIiIiISBLqdBARERERERGRJNTpICIiIiIiIiJJqNNB\nRERERERERJJQp4OIiIiIiIiIJKFOBxERkcVkZiea2esJ8582s++lyu+PzOxhM/tJp+sQERGRNIZ3\nugAREZEK6cp+UtkDeDVhvoiIiEifUqeDiIhIP+Huj3a6BlmUmS0BzHP3lB1OIiIiA5I6HURERAoy\ns3WBp4EvAB8BPg/8A/g5cIy7L8jWOxE4Etga+AGwOTALONLdb83lPQ3c4O6HZ48nA6OAbwBnAx8E\nHgPGuvtDud9bDrgAGAO8BVwMvAKc6e5Ds3WGA6cCnwNWy5b/DjjA3RteMmJmI4FTgO2A1YG/AFcB\nJ7n7O7n1FgDHAMsAY4FhwA3AOHd/O7feNsD3gX8FngCO7uUtztfydWA88D7gBeAi4Dvu3pX7O3zW\n3a+t+70HAXf3z2eP1wROB3YBls3eg/F17+fTwI3AbGAcsBawavaeiYiISAs0p4OIiEh53wbeBfYm\nOhWOBL6SW94FjAD+B/gpcRnFS8DVZrZCD7ldwEjgXOKL8t7AUsC1ZjYst95kYDfgKOBLwIbA4XS/\nFORbwNeA7wA7EV+mnweW7OH1VyYu9ziS+JJ+OvDF7N9YbxywQbb8JGB/4L9rC81sNeAWolPks8CZ\nWc6aPbx+7XcPy9a9GfgU8R6emNWDuz8L/AbYt+73PkB08Pw8e7w8cC+wSVbvnsCbwO1mtnLdy+4F\nfJJ4Hz+drSciIiIt0kgHERGR8n7j7t/M/v92M9uB+GL9o9w6I4jRD9MAzOxPxNn5XYHLesheAfiY\nu8/Mfu8t4A5gK+A+M9uI6MQ4wN0vy9aZBsysy/kwcKu7X5h77rqe/lHu/geiI4Ms9z6i02CymY1z\n93/kVn/e3b+Q/f+tZjYqew++lT03HlgA7Orub2R5fwFu76kGMxtKdF5c5u7js6dvM7MlgSPM7FR3\nfxW4HDjNzJZ191oHwX7E6ITaaJLxwHLAKHf/e5Z/OzHq4ijg2NxLDwc+UfdvFBERkRZppIOIiEh5\nv6p7/DgxJD9vAbkv2NnZ+bcbrFfv+VqHQy57SO73tiRGNNyQy+72OPMQsJuZnWBmW5jZkF5eFwAz\n+6aZPZZ1dswjRg0MB9avW/W2usf178GWwJ21Doeszjvp/ZKFDYkRF1fXPX8FMUpjy+zxldnjPXLr\n7ANc4+7zs8c7AXcCc8xsWDZapAuYTnTK5N2lDgcREZHy1OkgIiJS3py6x+8Ql0HkvZ378tvTeouT\nTe73RhKTHNbPy/BS3eNvs/DyiN8CfzWz43t6YTMbD5xFjIgYQ3wxH1f3+j3Vmb90Y/UGNTWqs94K\nRMfAi3XP1x6vCODuLxIdCvtltW8KbER2aUVmZaJTYl7u5x3gAGDtJvkiIiJSgi6vEBERqbYXgBFm\n9p66jofV8iu5+zzgZOBkM1sfOBg40cyecvf8F/O8zwJT3X1C7Qkz27hEnas2eL7Rc3mvECM76tdb\nLbe85nLggmyejH2JUSJ312U9AUzIMvPm1j3WnSpERETaQJ0OIiIi1fYg8QX608RElWSXTuze7Bfc\nfRYwwcwOIUYDNLM0C0dW1BxQsM4HgEPynSPZ3Bcr9vJ7DvyNmERzau75fYiOggdyz10LnJ+tuw9x\nCUbebcQdRmbm76ohIiIi6ajTQUREpMLc/XEzuw74vpktCzxL3KViKXJn67N1ZgAPE3diGAMsT88T\nOf4KONzMxgF/Ijoc3l+w1HOISzNuMbPTiM6GE4GXe/old19gZhOBc83sb8BNxK1HjwYmZZNI1tad\nk02ieTxxOUf9BJ2TiLtq3G1m5xK3xFyFmJTzOXc/t+C/TURERJrQnA4iIiKtqR92v7jD8But1yhr\ncfLrnzuImDjyTOBS4CniNpr/l1vnHmL0w8+A64GPAftnkzk2czLxxf0k4tKFt4DDmtTT4/vg7n8F\nPkF0hlwJ/CdwKPCXnn4v+93zgLHEnT5uIP69x7v7MQ1Wv5zocHjS3WfU5bwCfIToeDkNmEZ0RKxL\nzHOx2P8eERERWTxDurp0TBURERlozOxuYoLJHTtdi4iIiAxeurxCRESk4sxsT2Ad4PfAssQlBNvS\n/faRIiIiIn1OnQ4iIiLV9wbwBWADYAlgJvB5d7+ho1WJiIjIoKfLK0REREREREQkCU0kKSIiIiIi\nIiJJqNNBRERERERERJJQp4OIiIiIiIiIJKFOBxERERERERFJQp0OIiIiIiIiIpKEOh1ERERERERE\nJAl1OoiIiIiIiIhIEup0EBEREREREZEk1OkgIiIiIiIiIkn8Pzt8XrmPDIjXAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc707a9c2e8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax1 = plt.subplots(figsize=(12,6))\n",
    "ax2 = ax1.twinx()\n",
    "labels = np.array(out_df['innings_over'])\n",
    "ind = np.arange(len(labels))\n",
    "width = 0.7\n",
    "rects = ax1.bar(ind, np.array(out_df['total_runs']), width=width, color=['yellow']*20 + ['green']*20)\n",
    "ax1.set_xticks(ind+((width)/2.))\n",
    "ax1.set_xticklabels(labels, rotation='vertical')\n",
    "ax1.set_ylabel(\"Runs in the given over\")\n",
    "ax1.set_xlabel(\"Innings and over\")\n",
    "ax1.set_title(\"Win percentage prediction for Sunrisers Hyderabad - over by over\")\n",
    "\n",
    "ax2.plot(ind+0.35, np.array(out_df['predictions']), color='b', marker='o')\n",
    "ax2.plot(ind+0.35, np.array([0.5]*40), color='red', marker='o')\n",
    "ax2.set_ylabel(\"Win percentage\", color='b')\n",
    "ax2.set_ylim([0,1])\n",
    "ax2.grid(b=False)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "_cell_guid": "07f54470-9a9c-6e7a-395d-fcd5080d89ec"
   },
   "source": [
    "Hurray.! Things are more clear now.\n",
    "\n",
    "As we can see, SRH has scored lot of runs in the last two overs (16 and 24),  which clearly gave them an edge.\n",
    "\n",
    "Also the scoring rate of RCB was very low in the first 8 overs which made the win probability to hover over 0.5. Then 9th over changed the dynamics since RCB scored 21 runs in that over clearly giving them an edge. \n",
    "\n",
    "Wickets that went away in the 13th to 15th overs helped SRH increase the win percentage. In 16th over SRH conceded only 4 runs which shifted the game in their favour.!\n",
    "\n"
   ]
  }
 ],
 "metadata": {
  "_change_revision": 427,
  "_is_fork": false,
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}
